Deep Learning and its Applications

Name: Deep Learning and its Applications
Rating: 5 (1 reviews)

Dr. S. Manikandan · Dr. Gamidi. Lakshmi Vara Prasad · Mr. Vivekanandhan VijayaRangan

Dec 2022 · Quing Publications

5.0

1 review

Ebook

122

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About this ebook

Deep Learning and its Applications book chapter is intended to provide various deep insight about Deep learning in various applications. According to current Industry 4.0 standards, Deep learning on the emerging research area to give various services to IT and ITeS. In this book chapter various real time applications are taken for evaluating deep learning approach. Deep Learning is the subset of machine learning which has further learned results of artificial intelligent applications. Artificial Intelligent is the current scenario for making effective decisions. Here the applications are medical image processing, moving objects, image analysis, classification, clustering, prediction, and restoration used to identify various results. Based on each chapter different problems are taken for evaluation and apply different deep learning principles to find accuracy, precision, and score functions. Supervised and Unsupervised learning techniques, TensorFlow, Yolo classifier and Colabs are used to simulate the applications. In this book chapters are very useful for researchers, students, and faculty community to learn about Deep Learning in current trends.

Ratings and reviews

5.0

1 review

Arul Edison Anthony Raj Iroudayanadane

March 9, 2023

I read this book chapter on a deep learning , one of the emerging areas. Most researchers are researching various applications related to AI and ML. This chapter is classified based on medical imaging, moving objects, data visualization, multimodal aggregation, etc. Each chapter is written continuously, and fully connected. Each chapter clearly took the recent dataset, evaluation metrics, inputs, processing stages, connected process, & results. So, a reader can understand each other's values & information, which means it can be selected by an operating data process and multiple objects related to series effects. I recommend this book to my students.

About the author

Dr. S. Manikandan is working as an Associate Professor & Head / Chairman (Board of Studies) of Information Technology in E.G.S Pillay Engineering College (Autonomous), Nagapattinam. He completed Ph.D. from Anna University in the year of 2020, M.E. (CSE) with University Rank Holder and Distinction from Annamalai University in the year of 2012 and B.Tech., (IT) with Distinction from E.G.S. Pillay Engineering College in Nagapattinam in the year of 2010. Also, he is a member of IEEE, ACM, MIE, CSTA, IAENG, CSI and ISTE. Currently, he is doing research in Artificial Intelligence, Deep Learning and Data Analytics. He is a recognized supervisor at Anna University.

Dr. Gamidi. Lakshmi Vara Prasad received Ph.D. and M.Tech., from Bharath University in 2020 and 2012, respectively. Currently, he is an Assistant Professor in the Department of CSE, School of Technology, GITAM Deemed to be University, Hyderabad. He has published more than 30 research papers in international journals. He also presented the paper in 15 international conferences and 5 national conferences. He received the National Eminent Researcher Award from the International Institute of Organized Research in the year 2020. He is a life member of many professional bodies like CSI, IAENG, SDIWC and CSTA.

Mr. Vivekanandhan VijayaRangan received his bachelor’s degree in Computer Science and Engineering from Anna University in 2010, master’s degree in Computer Science and Engineering from Annamalai University in 2012. Currently, he is pursuing his Ph.D., in the field of Wireless Sensor Networks. He has 10 years of teaching experience, and he is working as Assistant Professor in Computer Science and Engineering at Malla Reddy Institute of Engineering & Technology (Autonomous), affiliated to Jawaharlal Nehru Technological University Hyderabad, located in the Secunderabad, Telangana. His research interests include Wireless sensor network, Image Processing, Neural Network, Deep Learning, Machine Learning, Computational Intelligence and Computation. He is a life member of IEI.

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