Machine learning research papers ieee. ca/trkow/the-voice-kids-uk-judges.

, malicious users have also exploited them for unlawful or nefarious purposes. The cardiovascular system plays a vital role in all living organisms, responsible for circulating blood throughout the body, delivering essential oxygen and nutrients to cells, and eliminating waste products. Many traffic accidents can be avoided if sleepy drivers were given early warnings. The The development and exploitation of several prominent Data mining techniques in numerous real-world application areas (e. IEEE :Machine learning approach for brain tumor detection: 7. Various Cardiovascular disease refers to any critical condition that impacts the heart. This work presents several machine learning approaches for predicting heart diseases, using data of major Employee attrition is one of the biggest challenges faced within business organizations. This paper reviews various Machine learning approaches in detection of fake and fabricated news. The cyberspace has become more vulnerable to automated and prolonged cyberattacks. Various machine learning techniques and statistical Aug 22, 2020 · In general, agriculture is the backbone of India and also plays an important role in Indian economy by providing a certain percentage of domestic product to ensure the food security. Because heart diseases can be life-threatening, researchers are focusing on designing smart systems to accurately diagnose them based on electronic health data, with the aid of machine learning algorithms. Our experimental results have shown that our LSTM model outperforms previous models in spam detection with an accuracy of 98. Our paper deals with the impact of recent advances in data analytics, and how they can be leveraged for the healthcare sector, with specific emphasis on Machine Learning (ML) is now influencing every part of the industry. Also, Alpha-Beta Pruning algorithm is implemented to The use of massive clinical data in the medical field for supporting medical decision support is an inevitable development trend. The Logistic Regression, Random Forest, Gradient . Due to the lack of observable signs, this quiet invader often goes undetected in the beginning, leaving women susceptible to its sneaky development. Machine learning (ML) plays a significant role as it has decision support tool for Crop Yield Prediction (CYP) including Brain tumours pose a significant health risk, and early detection plays a crucial role in improving patient outcomes. Because of the high volume of data that being generated by devices, sensors and social media users, the machine can learn to distinguish the pattern and makes a reasonably good prediction. The paper employs a novel combination approach of Machine learning based estimator with artificial intelligence (AI) to build chess AI. With millions of transactions taking place, it is practically impossible to detect frauds manually with good speed and accuracy. However, it is more widely used for classification prediction. While previous research has primarily focused on leaf-based disease detection, this paper proposes an automated stem disease detection and classification model using digital image processing and machine learning techniques. STT allows for the conversion of spoken language into written text, while TTS enables the generation of natural-sounding speech from written text. g. Papers representing each method were indexed, read, and IEEE :Credit card fraud detection using Machine Learning Techniques: 4. It employs two distinct datasets, one for fault detection and the other for fault classification. IEEE :Supervised Machine Learning Clean water is one of the basic needs of everyday life. Sales forecasting allows corporations to efficiently allocate resources including cash flow, production, and make better informed business plan. The study focuses on popular machine See full list on ieeeaccess. accounting for the majority of all cancer diagnoses and deaths. Advanced ml has become a significant industrial trend with highly specialized implications. This paper first introduces the key concepts and main content of natural language processing, and briefly When a student chose a college, there are various factors that come into the picture. Hence beforehand detection, prediction and diagnosis of lung cancer has become essential as it expedites and simplifies the consequent clinical board. The goal was Read all the papers in 2023 IEEE International Conference on Machine Learning and Applied Network Technologies (ICMLANT) | IEEE Conference | IEEE Xplore Aug 24, 2016 · In machine learning, a computer first learns to perform a task by studying a training set of examples. Our data set consists of various features relating to the Bitcoin price This paper aims to use various machine learning algorithms and explore the influence between different algorithms and multi-feature in the time series. Instance Paradigm Contrastive Learning for Domain Generalization. This study reviewed articles published in There is a renewed interest in the recent times for research and development in the field and subfield of Artificial Intelligence, and this is especially true for Machine Learning and Natural Language Processing. Blessing to the country is the overwhelming size of the agricultural sector. The proposed system is designed and developed to easily facilitate the detection of cataract, glaucoma and retinal diseases among patients. The author intends to highlight the merits and Sep 15, 2022 · Recent works discuss machine learning applications in disaster management, growing exponentially. It faces however some challenges due to the limited resources such as datasets and processing and analysing techniques. At design time, a large design space needs to be explored to find an implementation that fulfills all specifications and then optimizes metrics like energy, area, delay, reliability, etc. This evolution is enabling large-scale agricultural production processes to operate independently, thus, securing the food supply chain for an ever-growing population Mar 22, 2021 · These statistics motivate us to study on machine learning in this paper, which can play an important role in the real-world through Industry 4. Significant advances in object detection have been achieved through improved object representation and the use of deep neural network models. The two types of performance are Ovarian cancer is the type of cancer that has the highest recurrence rate in women and poses a serious threat to women. The machine learning algorithms in particular ANN and SVM are used as soft computing techniques for landslide prediction. There is no common system where one analysis can perform more than one disease prediction. To solve this problem, research is done using a machine learning model. We have used the USA's medical cost personal dataset from kaggle, having 1338 entries. Furthermore, the field of deep Oct 6, 2020 · This paper presents a critical assessment analysis on mental health detection in Online Social Networks (OSNs) based on the data sources, machine learning techniques, and feature extraction method. Now, the ML is touching the healthcare sector. The previously used security systems are no longer sufficient because cybercriminals are smart enough to evade Aug 12, 2020 · A comparison between the proposed deep learning model and twelve machine learning and ensemble learning methods based on relatively small data including 183 healthy individuals and 401 early PD patients shows the superior detection performance of the designed model, which achieves the highest accuracy, 96. Many techniques have been used to detect anomalies. It is playing a vital role in many fields like finance, Medical science and in security. ieee. On the other hand, with the advancement of science and technology, graphics have been an indispensable medium of information transmission, and image processing technology is also booming. The outcome is fatal, as it results in death. However, having long-term stress, or a high degree of stress, will hinder our safety and disrupt our normal lives. Crops are recommended based on soil, weather, humidity, rainfall, and other variables to increase agricultural output. This paper presents the work done by various authors in the field of machine learning in various application areas. Cyber security techniques provide enhancements in security measures to detect and react against cyberattacks. Machine Learning is Omni present and is widely used in various applications. The aim of this research paper is to enhance the overall performance of the system by introducing a student placement prediction system. Predicting cardiovascular diseases holds significant importance in clinical data analysis. To do this, we carried out a collection of This research paper addresses the challenge by developing and deploying machine learning enabled data driven & Electroencephalogram biosensor integrated mobile application that proactively gleans User’s stressful episodes, infuses collaborative intelligence derived from de-identified yet User relevant demographical, physiological, lifestyle May 2, 2021 · The goal of this article is to provide a holistic overview of relevant communication and machine learning (ML) principles, and thereby present communication-efficient and distributed ML frameworks with selected use cases. This paper aims to present comparison of the largely popular machine learning algorithms and techniques commonly used for breast cancer prediction, namely Random Forest, kNN (k Aug 15, 2024 · The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery. This article will explore the use of machine learning and its methodologies. Most of the students across the world are always in confusion after they complete higher secondary and the stage where they have to choose an appropriate career path. This paper focus on the survey of the few machine learning algorithms and techniques used in many applications and domains in detail. Stress affects every aspect of a person's life such as emotions, thoughts, and behaviors. For the first phase of our investigation, we aim to understand and identify daily trends in the Bitcoin market while gaining insight into optimal features surrounding Bitcoin price. Every institution strives to have a strong Placement team. The The popularity and usage of Cloud computing is increasing rapidly. In this work, Support Vector Regression (SVR) and Long-Short Term Memory (LSTM) techniques are used to predict the closing price from five different Trends in artificial intelligence have only realized their potential when backed up with datasets of the requisite scale, due to the data-hungry nature of machine learning algorithms. With the increasing availability of digital platforms and e-commerce websites, the fashion industry has transformed, and the way one shops for clothing The application of machine learning in stock market forecasting is a new trend, which produces forecasts of the current stock marketprices by training on their prior values. As we pass through the stages, we realize that every student Dec 24, 2022 · This paper addresses one of the most significant medical problems because of its challenging and subjective human interpretation. With growing population, it gets further difficult to diagnose and start treatment at early stage. In today's competitive job market, students often face challenges in understanding their strengths, identifying required skills, and effectively positioning themselves for job opportunities. The Journal of Machine Learning Research (JMLR), established in 2000, provides an international forum for the electronic and paper publication of high-quality scholarly articles in all areas of machine learning. Nowadays especially in this pandemic situation, there is a necessity for academic management to incorporate and change all study methods online. In the age of Machine Learning (ML), recommender systems In the evolution of artificial Intelligence (AI) and machine learning (ML), reasoning, knowledge representation, planning, learning, natural language processing, perception, and the ability to move and manipulate objects have been widely used. In this paper, we applied various machine learning and deep learning techniques for SMS spam detection. 9 million people die every-year due to this. We extract consumption mark, frequency and other features. Therefore, we have tried to create a base for future researches in the area so that the researchers can overcome the existing problems. The ultimate objective is to extract meaningful information from published abstracts. In this paper author intends to do a brief review of various machine learning algorithms which are most frequently used and therefore are the most popular ones. sakanaai/ai-scientist • • 12 Aug 2024 This approach signifies the beginning of a new era in scientific discovery in machine learning: bringing the transformative benefits of AI agents to the entire research process of AI itself, and taking us closer to a world where endless affordable creativity and innovation can The Student Placement Prediction and Skill Recommendation System is an innovative application designed to assist students in enhancing their employability and securing suitable job placements. One of the increasingly significant techniques is Machine Learning (ML), which plays an important role in this area. The Minimax Algorithm is a decision theory-based technique implemented for reducing the load on the chess engine’s hardware. In addition, farmers find it difficult to decide which crop is best suitable and profitable for their soil, in spite of the few technological solutions that exist today, due Pervasive growth and usage of the Internet and mobile applications have expanded cyberspace. kNN groups the data into coherent clusters or subsets and classifies the newly inputted data based on its similarity with previously trained data. With the advancement in machine learning, various research papers brought into light the numerous reasons why an employee leaves, this paper puts forward a machine learning pipeline that not only predicts employee attrition but also suggests a minimum cost approach for the company so that the employee does Jul 15, 2021 · The main objective of this research is to predict the possible presence of diabetes -specifically in females-at an early stage using different machine learning techniques. We see long articles in news websites, blogs, customers' review websites, and so on. Concentrating on the results of predictions of the models of machine learning There exists a large and rapidly growing body of literature related to applications of machine learning to Covid-19. The proposed paper presents an overview of various works being done on building an efficient IDS using single, hybrid and ensemble machine learning (ML) classifiers, evaluated using seven different datasets. We have used five different machine learning (ML) algorithms in this paper Gradient Boosting(GB), Random Forest(RF), K-nearest neighbors (KNN), Logistic Regression(LR) and Support Vector Machine(SVM) has been used for the development of the model. We propose a system that provides a robust, cost effective Ensuring the explainability of machine learning models is an active research topic, naturally associated with notions of algorithmic transparency and fairness. Traditionally, phishing attempts were carried out through wide-scale spam campaigns that targeted broad groups of people indiscriminately. Despite the fact that India has a large number of weather stations, they are mainly located in inhabited regions such as cities, suburbs, or towns. Machine learning (ML) has been shown to be effective in assisting in making decisions and predictions from the large quantity of data produced by the healthcare industry. Early detection measures have proven valuable in making critical decisions for high-risk In this paper, we attempt to predict the Bitcoin price accurately taking into consideration various parameters that affect the Bitcoin value. Timely identification of Alzheimer's disease can be beneficial for us to get necessary care and possibly even avert brain tissue damage Oct 19, 2017 · Machine learning is used in various fields such as bioinformatics, intrusion detection, Information retrieval, game playing, marketing, malware detection, image deconvolution and so on. Apr 20, 2017 · Consequently, this paper compiles, summarizes, and organizes machine learning challenges with Big Data. It has capability to learn by its own without seeking any help from human beings or without any explicit programming based on its previous experience and knowledge. Sep 4, 2020 · With the development of machine learning for decades, there are still many problems unsolved, such as image recognition and location detection, image classification, image generation, speech recognition, natural language processing and so on. 45% on average. But due to the recent advancement in technology, Machine Learning techniques have accelerated the health sector by multiple researches. Machine learning is emerging as a ray of hope Read all the papers in 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA) | IEEE Conference | IEEE Xplore Many of the existing machine learning models for health care analysis are concentrating on one disease per analysis. The rapid advancements in natural language processing provides strong support for machine translation research. The agricultural industry is also evolving in line with the implementation of modern communication protocols, intelligent sensors, and equipment. Mental May 15, 2018 · With the development of the Internet, cyber-attacks are changing rapidly and the cyber security situation is not optimistic. This makes weather forecasting in isolated regions more imprecise, which can be inconvenient for individuals such For modern retail corporations operating a huge chain of businesses, exact sales predication is the key in driving corporations development, even success or failure. The objective of this paper is to predict the accurate stock prices which helps the investors to make more accurate and informed investment decision. The appropriateness of the mental health detection was also investigated by identifying its data analysis method, comparison, challenges, and limitations. In this paper, a real-time visual-based driver drowsiness detection system is The objective of this research paper is to make a simple yet effective one-stop solution for phishing detection and prevention system using machine learning and making an intelligent web browser plugin and to study different machine learning models and approaches with which we can come up with an efficient product. Various papers have been studied for different methods that have been used so Now-a-days everyone wish to live in the large cities but the competition in the market related to all the resources is increasing day by day. It is now an area of interest for more doctors and scientists to implement different techniques and harvest the power of ML. Starting from IP traffic classification, filtering malicious traffic for intrusion detection, ML is the one of the promising answers that can be effective against zero day threats. Mainly it can make its own decisions or can predict in performing certain tasks based on the res pective input dataset and Credit card fraud detection is presently the most frequently occurring problem in the present world. Sentiment analysis is a method of data mining that evaluates textual data consuming machine learning techniques. Financial services are used everywhere and function with high complexity. e. In this paper, we provide the most up-to-date review as of the beginning of 2022. We propose a unifying terminology with two central elements: (i) client risk profiling and (ii) suspicious India is the land of agriculture and is among the top three global producers of many crops. This article presents a brief overview of machine-learning technologies, with a concrete case study from code analysis. Recently, there has been a rising trend of employing unsupervised machine learning using unstructured raw network data to improve network performance and provide services, such as traffic engineering, anomaly detection, Internet traffic Dec 3, 2020 · We further discuss various diseases along with corresponding techniques of AI, including Fuzzy Logic, Machine Learning, and Deep Learning. As machine learning plays a vital role in the easiness of human life, this paper also uses Machine Learning (ML) algorithms to screen Mental Health by using a Mental Disorder Questionnaire (MDQ). ML techniques have been used in This paper represents the work of a new integrated and collaborative Smart application for managing students online through data mining techniques. This paper presents a comprehensive review of current literature on drone detection and classification using machine learning with different modalities. Now a Day, a huge increase in demand for machine learning has been seen with the great number of available datasets Nowadays, Machine Learning (ML) has become a trending technology in almost all fields of research. Due to the growing connectivity between computers, intrusion detection becomes vital to perform network security. Several companies are investing in this field either for their own use or to provide it as a service for others. This paper addresses a detailed discussion on machine learning models for disaster management and its various stages, such as recovering and consolidating information, searching and rescuing, and post-disaster assessment. We propose an application-based taxonomy to group the existing literature and provide an Agriculture plays a vital role in the economic growth of any country. org Email Spam has become a major problem nowadays, with Rapid growth of internet users, Email spams is also increasing. In this paper, an effort has been trying to coin up Machine Learning to predict the stock prices. To improve traffic safety, this As an essential part of artificial intelligence technology, natural language processing is rooted in multiple disciplines such as linguistics, computer science, and mathematics. Early detection of diabetes can significantly prevent the progression of the disease and reduce the risk of serious complications such as heart and kidney diseases, making the proper lifestyle changes at the right time can Weather forecasts have grown increasingly significant in recent years since they can save us time, money, property, or even our lives. This paper presents the utilisation of machine learning Sep 16, 2022 · Ensemble learning techniques have achieved state-of-the-art performance in diverse machine learning applications by combining the predictions from two or more base models. Building a model and then passing the past data as input that is as training data to the model based on the results acquired need to consider an algorithm which gives better accuracy and response time and Breast cancer is diagnosed in over 2 million people worldwide each year. no code implementations • IEEE Transactions on Circuits and Systems for Video Technology 2024 • Zining Chen, Weiqiu Wang, Zhicheng Zhao, Fei Su, Member, IEEE, Aidong Men, and Yuan Dong Mar 7, 2020 · This paper proposes a rainfall prediction model usi the proposed machine learning model provides better results than the other algorithms in the literature Agriculture is the pillar of the Indian economy and more than 50% of India's population are dependent on agriculture for their survival. Addressed technologies encompass radar, visual, acoustic, and radio-frequency Machine Learning (ML) has been applied in this regard in different types of networks and networking technologies to meet the requirements of future communicating devices and services. In this article proposing a system which used to predict multiple diseases by using Data pre-processing is considered as the core stage in machine learning and data mining. This review paper presents various approaches to generate summary of huge texts. 0 automation. The Indian farmer lies at the heart of the agricultural sector yet most Indian farmers remain at the bottom of the social strata. In this research, there are two types of Questionnaires employed. This paper presents a concise overview of ensemble learning, covering the three main ensemble methods: bagging, boosting, and stacking, their early development to the recent state-of-the-art algorithms. The alarming cases of these diseases call for an urgent intervention by early diagnosis. One of the results of Cloud development is the emergence of various security problems for both industry and consumer. In this research paper, we conduct a Systematic Literature Review (SLR) which analyzes ML models that detect anomalies in their This paper focuses on the vital task of utilizing Machine Learning techniques for fault detection and fault classification in electrical power transmission lines. Machine learning is used to discover patterns from medical data sources and provide excellent capabilities to Image recognition has become a prominent area of research in recent years, and the development of deep learning models has significantly improved the accuracy of image classification tasks. One of the ways to secure Cloud is by using Machine Learning (ML). Mental stability can be affected by different situations - illness can affect the individual's emotion, thoughts, attitude and decision making. , according to cancer research. To erect the progress and medication of cancerous conditions machine learning techniques have been utilized because of its accurate outcomes. Thus, the objective of this paper is to Sep 11, 2023 · Large blocks of data must be analyzed and explored by utilizing the data mining procedures in order to uncover significant patterns and trends. This is The most frequently occurring cancer among Indian women is breast cancer. In this research paper, we propose a machine learning- based house pricing prediction model that can predict the prices of houses more accurately. Jul 15, 2020 · The articles in this special section are dedicated to the application of artificial intelligence AI), machine learning (ML), and data analytics to address different problems of communication systems, presenting new trends, approaches, methods, frameworks, systems for efficiently managing and optimizing networks related operations. The prospective applications of machine learning technology in healthcare are discussed in this article, along with a number of industry-wide projects. These features enable the creation of intelligent mechanisms for decision support to overcome the limits of human knowledge processing. Massive amounts of data are produced by hospital information systems (HIS), yet it Artificial Intelligence (AI) has been growing considerably over the last ten years. People are using them for illegal and unethical conducts, phishing and fraud. As communication technologies and equipment evolve, smart assets become smarter. In this work, we propose a system for Fake news Jan 16, 2021 · Many researchers have used various Machine Learning and Deep Learning techniques to detect and predict Alzheimer's. This is due to the rise in both online transactions and e-commerce platforms. This survey report describes key literature surveys on machine learning (ML) and deep learning (DL) methods for network analysis of intrusion detection and provides a brief tutorial description of each ML/DL method. Computer-aided detection or diagnosis (CAD) systems plays a major role in prior identification of breast cancer and can be used for reduction of death In recent years, machine learning has been used to create data-driven solutions to problems for which an algorithmic solution is intractable, as well as fine-tuning existing algorithms. In this article, we provide a detailed account of current research on the application of ML in communication networks and shed light on future research challenges. An automated Fraud Detection System is thus required. This research paper seeks to examine the effects of Min-max, Z-score, Decimal Scaling, and Logarithm to the base 2 on the accuracy of J48 classifier using the NSL-KDD dataset. We have used the UCI heart failure prediction dataset for this research work. Machine learning is a real thing While machine learning and artificial intelligence have long been applied in networking research, the bulk of such works has focused on supervised learning. In addition, ML This research paper presents a rule-based recommender system for analyzing and forecasting student performance in education. In the present world, we are facing a lot of Read all the papers in 2022 International Conference on Machine Learning and Knowledge Engineering (MLKE) | IEEE Conference | IEEE Xplore Machine learning can bring a boom in the agriculture field by changing the income scenar This paper focuses on predicting the yield of the crop by applying Machine learning is a branch of artificial intelligence that aims at enabling machines to perform their jobs skillfully by using intelligent software. To train the machine, various kinds of machine learning algorithms and tools are available. This paper aims to benchmark multiple machine learning methods such as k-nearest neighbor (KNN), random forest and support vector machines (SVM), while the deep learning methods such as autoencoders, convolutional neural networks (CNN), restricted boltzmann machine (RBM) and deep belief networks (DBN). we used a dataset from UCI and build a spam detection model. A model has been developed to recognize keywords and extract pertinent information from job requirements provided by recruiting companies. With the increase in online transacting, frauds too are increasing alarmingly. Creating a fake profile and email account is much easy for the spammers, they pretend like a Breast cancer is one of the most common and leading causes of cancer among women. At the age of 18, the students don’t have adequate maturity to accurately know about what an individual has to follow in order to choose a congenial career path. The agriculture sector is also a significant contributor factor to the country's Gross Domestic Product (GDP). Online recommender systems are being used increasingly often for hospitals, medical professionals, and drugs. In the field of deep learning research, the research on image classification has always been the most basic, traditional and urgent research direction Driver drowsiness is one of the leading causes of traffic accidents and has a substantial impact on road safety. With its ability to make predictions by relying on the data rather than any explicit instructions Machine Learning and Deep Learning Techniques have been employed and adapted in many The paper presents the development and the comparison of multiple recommendation systems, capable of making item suggestions, based on user, item and user-item interaction data, using different machine learning algorithms. Industry, Healthcare and Bio science) has led to the utilization of such techniques in machine learning environments, in order to extract useful pieces of information of the specified data in healthcare communities, biomedical fields etc. Machine learning has played a vital role in classification of the information although with some limitations. The test result shows that the design is accurate and robust for seeing the road lane. Fake news detection is an emerging research area which is gaining big interest. This paper examines more closely how object detection has evolved in the era of deep learning over the past years. Nonetheless, there is little scientific literature on statistical and machine learning methods for anti-money laundering. Drowsiness detection systems monitor the driver condition and generate an alarm if drowsiness signs are detected. Today, the great majority of consumers look online before asking their doctors for prescription suggestions for a range of health conditions. IEEE papers on Python Machine Learning final year projects IEEE Machine learning projects for final year with source code in Python IEEE projects for CSE 2023 2024 What is Machine Learning? Basically, An ML model is defined as a computer-intensive mechanism and applies resampling and iterative methodologies for classification approaches. Designing Chess Engine has been a main focus of research for a long time. The accurate analysis of medical Machine Learning is subset of Artificial Intelligence and there is lots of research growth across the world. This article provides an overview of different sensor modalities, such as cameras, radars, and light detection and ranging (LiDAR) used commonly for perception, along Detecting objects remains one of computer vision and image understanding applications’ most fundamental and challenging aspects. In pursuing this objective, the ML techniques are utilized to classify different publications into three fields: Science, Business, and Social Science. Sending malicious link through spam emails which can harm our system and can also seek in into your system. Over the past This paper represents a machine learning-based health insurance prediction system. Students generally look for the outcome and, in this case, it is being placed. By considering all these conditions this research is focused to discuss the solution to manage and —The revolutionary advances in machine learning and data mining techniques have contributed greatly to the rapid developments of maritime Internet of Things (IoT). Housing price prediction is a challenging task due to the complexity of huge data variance with changes in location points. Like one analysis if for diabetes analysis, one for cancer analysis, one for skin diseases like that. There is a new case of Alzheimer's disease being discovered globally in every four seconds. The limitation of such and approaches and improvisation by way of implementing deep learning is also reviewed. In this paper, we provide an extensive literature review highlighting the main techniques used to detect malicious URLs that are based on machine learning models, taking into consideration the limitations in the literature, detection technologies, feature types, and the datasets used. With the increase of population, frequent changes in climatic conditions and limited resources, it becomes a challenging task to fulfil the food requirement of the present population. JMLR has a commitment to rigorous yet rapid Sep 3, 2020 · The six papers in this special section focus on machine learning for computer systems. Prior identification is the best way to manage breast cancer results. A dataset comprising 3789 images of diseased and Nov 12, 2022 · Driving vehicles on roads in conditions such as fuzzy view, showery, and inside the tunnel is difficult for a driver. Normalization, discretization, and dimensionality reduction are well-known techniques in data pre-processing. IEEE :Leveraging Deep Preference Learning for Indexing and Retrieval of Biomedical Images: 6. The proposed framework utilizes demographic data, academic abilities, and psychological characteristics of the students to identify areas for improvement and provide helpful recommendations for optimizing their academic outcomes. This paper is a The phenomenon of Fake news is experiencing a rapid and growing progress with the evolution of the means of communication and Social media. This paper assists Feb 24, 2022 · Over the last few decades, rapid progress in AI, machine learning, and deep learning has resulted in new techniques and various tools for manipulating multimedia. Even though AI/ML is considered a key technology for next For the past few years, fast fashion has become very popular, which has had a great impact on the textile and fashion industries. Also, the paper deals with finding different ways of using machine learning models to create recommendation systems This research paper introduces a cutting-edge solution that harnesses state-of-the-art technologies, including Machine Learning and Natural Language Processing (NLP), in conjunction with cosine similarity. There is a chance of fifty percent for fatality in a case as one of two women diagnosed with breast cancer die in the cases of Indian women [1]. This research study aims to explore the current state-of-the-art deep Stress is a major symptom for mental health. IEEE :Animal classification using facial images with score-level fusion: 5. In this paper, we focus on anti-money laundering in banks and provide an introduction and review of the literature. It is critical to achieving high levels of safety and autonomy in driving. Intrusion Detection is software or a device that scans a system or a network for a distrustful activity. This Dec 23, 2017 · The application of machine learning (ML) technique in cyber-security is increasing than ever before. Due to tremendous expanse of opinions of users, their reviews, feedbacks and suggestions available over the web resources, it Apr 9, 2022 · Phishing is an internet scam in which an attacker sends out fake messages that look to come from a trusted source. The focus of this project is to forecast the stock price of Reliance Jun 19, 2019 · Heart disease is one of the most significant causes of mortality in the world today. Early detection of breast cancer, combined with prompt and effective treatment, improves patients' prognosis and recovery Nov 24, 2017 · It is increasingly recognized that artificial intelligence has been touted as a new mobile. Jul 21, 2023 · Speech-to-Text (STT) and Text-to-Speech (TTS) recognition technologies have witnessed significant advancements in recent years, transforming various industries and applications. Mental disorders are becoming more common for the employees due to stress in their workplace. 17. This paper aims to implement Machine learning and Deep learning algorithms in real-time situations like stock price forecasting and prediction. Recently, an ongoing process has been shown to improve water quality, making water less suitable for use. It benefits not just farmers, but also the country and helps to keep food costs down. This paper provides an overview of deep learning techniques using two models in image recognition, including deep belief network and convolutional neural network. We selected 37 publications indexed in arXiv and IEEE Xplore databases that train ML models on programming language data to generate code. Precision agriculture also known as smart farming have emerged as an innovative tool to address current challenges in agricultural The second detection is the anomaly detection which assumes malicious activity as any action that deviates from normal behavior. The Decision Tree Algorithm is used by Naïve Bayes algorithm in this type of machine learning to support drinking water quality. Early diagnosis will benefit from the use of automated methods, especially when a group of Mar 31, 2018 · Machine Learning is modern and highly sophisticated technological applications became a huge trend in the industry. When a person gets stressed, there are notable shifts in various bio-signals like thermal Apr 25, 2019 · In order to examine malicious activity that occurs in a network or a system, intrusion detection system is used. Our research paper [1 Jul 12, 2018 · To overcome this problem, train the machine to predict the future by itself with the help of training and test datasets. As per the recent study by WHO, heart related diseases are increasing. The statistical learning methods constitute the backbone of intelligent software that is used to develop machine intelligence. Therefore, a stock price prediction approach has Jan 8, 2022 · In recent years, there has been increasing research and analysis on the importance of mental health in achieving global sustainable development goals. One of the most major and notable advancements in the field of computer science has been the ability to the computer systems that they can act, think and make decisions like human being. New research is being done by use of statistical traffic characteristics and ML techniques. Early diagnosis is crucial for evaluating the likelihood of treatment, particularly in situations of fatal illnesses like melanoma, and it is quite expensive to diagnose. A URL or file will be included in the mail, which when clicked will steal personal information or infect a computer with a virus. Once it has advanced and its symptoms are obvious, it becomes arduous to treat. The computer then performs the same task with data it hasn't encountered before. With the deepening of people's research in this field, the application of machine learning is increasingly extensive. All published papers are freely available online. From detecting objects from an image to recommending different items while doing online shopping based on someone's recent browsing history. In this research paper, we provide a comprehensive review of the latest Due to the increasing size of integrated circuits (ICs), their design and optimization phases (i. In this review paper, we have analysed and compared the accuracy and the performance of deep learning models such as Recurrent Neural Networks (RNN), Long Short Term Memory (LSTM), Convolutional Neural Networks (CNN), DenseNet This paper suggests use of sentiment analysis classification as an effective method for examining textual data coming from variety of resources on internet. Credit card fraud generally happens when the card was stolen for any of the unauthorized purposes or even when the fraudster uses the credit card information for his use. Medical databases are one area where the data mining procedures can be utilized. As a result, securing websites is becoming more critical. However, in its early stages, it is still a curable cancer. The medical suggestion system can be valuable when pandemics, floods, or cyclones hit. This review paper comprehensively surveys the landscape of Generative AI, encompassing its foundational concepts, diverse models, training methodologies, applications, challenges, recent advancements, evaluation Machine learning is predominantly an area of Artificial Intelligence which has been a key component of digitalization solutions that has caught major attention in the digital arena. Many people all over the world are struggling with their health and medical diagnoses. Experiments were May 13, 2023 · ML has made considerable strides in recent years, with applications in many different fields of study and industry. Prediction of cardiovascular disease is a critical challenge in the area of clinical data analysis. The goal lies in increasing the So, spam classification has special attention. In contrast to other research that discusses challenges, this work highlights the cause–effect relationship by organizing challenges according to Big Data Vs or dimensions that instigated the issue: volume, velocity, variety, or veracity. 5%. presented a stress level classification framework using the PhysioBank dataset to analyze the stress Anomaly detection has been used for decades to identify and extract anomalous components from data. Medical decision support is based on a variety of data sources accumulated and acquired in real-time in the clinic, and various machine learning algorithms are used to achieve classification of patient disease types or prediction of disease risks. However, regrettable is the yield per hectare of crops in comparison to international standards. Currently, it has become the common health issue, and its incidence has increased recently. It is effective for classification as well as regression. However, the traditional image processing Journal of Machine Learning Research. However, this kind of investment possesses a lot of risks. The existing methods and techniques for handwritten digit recognition were reviewed and understood to analyze the most suitable and best method for Feb 14, 2022 · Machine learning is a relatively new field. Therefore, many works have been done to build a model using Machine Learning algorithm to try to predict the stock price values. Over time, various algorithms have been developed to make such machines and computer Agriculture and its allied sectors are undoubtedly the largest providers of livelihoods in rural India. For example, high-quality and realistic The rapid identification of plant stem diseases is crucial for implementing timely intervention and minimizing crop loss. We Generative Artificial Intelligence (AI) stands as a transformative paradigm in machine learning, enabling the creation of complex and realistic data from latent representations. Specialized computer systems have driven the performance and capability of deep learning over the past decade. Features in the dataset that are used for the prediction of Stress is a common part of everyday life that most people have to deal with on various occasions. In general, the effectiveness and the efficiency of a machine learning solution depend on the nature and characteristics of data and the performance of the learning algorithms. It is challenging to effectively estimate customer turnover because the majority of the existing projections use a single prediction model. In this work, different Machine Learning (ML) techniques are used and evaluated based on their performance of classifying peer reviewed published content. The prominent cause of cancer-related mortality throughout the globe is “Lung Cancer”. A middle-class family can’t afford the price of rent, food, water and electricity while surviving his family. At run time, a large configuration space needs to be Jul 8, 2023 · One significant problem that businesses face is customer attrition. Though the technology has been mostly used in legitimate applications such as for entertainment and education, etc. Fashion is an integral part of one's daily lives, and it has a significant impact on identity and self-expression. Most systems that use ML methods use them to perform predictive analysis. Detecting mental stress earlier can prevent many health problems associated with stress. It has become crucial for corporate operations and growth to prevent customer churn and work to keep clients. The proposed model uses a combination of data pre-processing techniques and machine learning algorithms simultaneously. This research paper aims to reveal some important insights into current and previous different AI techniques in the medical field used in today’s medical research, particularly in heart disease prediction More people invest their money in the stock market. We have also seen ML techniques being India is a predominantly agricultural country, with agriculture playing animportant part in the Indian economy and people’s lives. Additionally, the paper examines some of In the current era stock price prediction plays a key role for prediction of future data with respect to training the past data by using machine learning or deep learning technologies. This research area has emerged in the last few years due to the rapid development of commercial and recreational drones and the associated risk to airspace safety. While most approaches focus on the problem of making the model itself explainable, we note that many of the decisions that affect the model's predictive behaviour are made during data preprocessing, and are encoded as specific data The dominant causes of visual impairment worldwide are Cataract, Glaucoma, and retinal diseases among patients. Deep learning techniques have emerged as a promising approach for automated brain tumor detection, leveraging the power of artificial intelligence to analyse medical images accurately and efficiently. Variations in weather, climate, and other such environmental conditions have become a major risk for the healthy existence of agriculture. , rendering it a major public health issue. This review provides a broad and detailed overview of studies for code generation using ML. In this paper, we propose an efficient and accurate sales forecasting model using Oct 18, 2012 · The MNIST Database of Handwritten Digit Images for Machine Learning Research [Best of the Web] Abstract: In this issue, “Best of the Web” presents the modified National Institute of Standards and Technology (MNIST) resources, consisting of a collection of handwritten digit images used extensively in optical character recognition and machine Deep Learning, Machine Learning and Artificial intelligence are buzzwords that has piqued the curiosity of many researchers. The study focuses on Alzheimer's is a progressive brain disorder which is an untreatable, and inoperable and mostly affect the elderly people. , computer-aided design, CAD) grow increasingly complex. The study compares the effectiveness of the Sequential Neural Network (SNN) and K-Nearest Neighbors (KNN) for fault detection, and The task for handwritten digit recognition has been troublesome due to various variations in writing styles. This paper aims to conduct a literature review of trends and methods of machine learning used for predictive analysis. Machine Learning (ML) is probably the most popular branch of AI to date. This research describes a reliable method for recognising road lanes in real time. Mar 30, 2023 · Automotive perception involves understanding the external driving environment and the internal state of the vehicle cabin and occupants using sensor data. Given the substantial volume of research, there is a need to organize and categorize the literature. But now-a-days, food production and prediction is getting depleted due to unnatural climatic changes, which will adversely affect the economy of farmers by getting a poor yield and also help the farmers to remain Due to the plethora of data available today, text summarization has become very essential to gain just the right amount of information from huge texts. The price of the flats in the city is increasing and there is so much of risk to predict the actual price of the house. The real consumption records constitute the time series as the research object. The complexity of the road environment makes lane detection difficult. This research applies machine learning to the development of an improved finite-volume Since its beginning, optimization has played a vital role in data science. This systematic analysis might also make contributions to better expertise the considerable use of remotely sensed records and spatial evaluation techniques to conduct landslide research at more than a few scales. 1 However, as machine learning models and systems improve, there is a growing opportunity to also use these models to improve how we design, architect, optimize, and automate computer systems and Jan 25, 2023 · Money laundering is a profound global problem. Recently, many attempts have been made to solve this problem, as after Covid-19 pandemic, health insurance has become one of the most prominent areas of research. This paper presented the study on previous research on stress detection based on machine learning algorithms. Abstract: k-Nearest Neighbor (kNN) algorithm is an effortless but productive machine learning algorithm. ucvfdoxb utdxeg cwl qaaxfy gou bzg pawom kifc qzxr lacg