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Deep Learning Applications, Volume 4 de M. Arif Wani

Deep Learning Applications, Volume 4: Advances in Intelligent Systems and Computing, cartea 1434

Editat de M. Arif Wani, Vasile Palade
en Limba Engleză Paperback – 26 noi 2022
This book presents a compilation of extended versions of selected papers from 20th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2021). It focuses on deep learning networks and their applications in domains such as healthcare, security and threat detection, fault diagnosis and accident analysis, and robotic control in industrial environments. It highlights novel ways of using deep neural networks to solve real-world problems, and also offers insights into deep learning architectures and algorithms, making it an essential reference guide for academic researchers, professionals, software engineers in industry, and innovative product developers. The book is fourth in the series published since 2017.
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Specificații

ISBN-13: 9789811961526
ISBN-10: 9811961522
Pagini: 384
Ilustrații: XIV, 384 p. 155 illus., 124 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.68 kg
Ediția:1st ed. 2023
Editura: Springer Nature Singapore
Colecția Springer
Seria Advances in Intelligent Systems and Computing

Locul publicării:Singapore, Singapore

Cuprins

Identification of Human Papillomavirus from Super Resolution Microscopic Images Generated Using Deep Learning Architectures.- Evaluation of Sequential and Temporally-Embedded Deep Learning Models for Health Outcome Prediction.- Transfer Learning for Depression Screening from Follow-up Clinical Interview Questions.- Early Mental Health Uncovering with Short Scripted and Unscripted Voice Recordings.- A Comprehensive Analysis of Aspect Oriented Suggestion Extraction from Online Reviews.

Notă biografică

Dr. M. Arif Wani is currently a Professor at the University of Kashmir, having previously served as a Professor at California State University Bakersfield. He completed his M. Tech. in Computer Technology at the   Indian Institute of Technology, Delhi, and his Ph.D. in Computer Vision at Cardiff University, UK. His research interests are in the area of machine learning, with a focus on neural networks, deep learning, inductive learning, and support vector machines, and with application to areas that include computer vision, pattern recognition, classification, prediction and analysis of gene expression datasets. He has published many papers in reputed journals and conferences in these areas. Dr. Wani has co-authored the book ‘Advances in Deep Learning’, co-edited many books in ‘Machine Learning and Applications’ and ‘Deep Learning Applications’. He is a member of many academic and professional bodies.

Dr. Vasile Palade is currently a Professor of Artificial Intelligence and Data Science at Coventry University, UK. He previously held several academic and research positions at the University of Oxford - UK, University of Hull - UK, and the University of Galati - Romania. His research interests are in the area of machine learning, with a focus on neural networks and deep learning, and with main application to computer vision, social network data analysis and web mining, autonomous driving, smart cities, health, among others. Prof. Palade is author and co-author of more than 200 papers in journals and conference proceedings as well as several books on machine learning and applications. He is an Associate Editor for several reputed journals, such as IEEE Transactions on Neural Networks and Learning Systems, Neural Networks, Knowledge and Information Systems. He has delivered keynote talks to international conferences on machine learning and applications. Dr. Vasile Palade is an IEEE Senior Member.
 

Textul de pe ultima copertă

This book presents a compilation of extended versions of selected papers from 20th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2021). It focuses on deep learning networks and their applications in domains such as healthcare, security and threat detection, fault diagnosis and accident analysis, and robotic control in industrial environments. It highlights novel ways of using deep neural networks to solve real-world problems, and also offers insights into deep learning architectures and algorithms, making it an essential reference guide for academic researchers, professionals, software engineers in industry, and innovative product developers. The book is fourth in the series published since 2017.

Caracteristici

Describes novel ways of using deep learning architectures for real-world applications Describes new algorithms of deep learning networks for real-world applications Presents results of using deep learning models for selected applications