Handbook of Research on Deep Learning Innovations and Trends

Leading technology firms and research institutions are continuously exploring new techniques in artificial intelligence and machine learning. As such, deep learning has now been recognized in various real-world applications such as computer vision, image processing, biometrics, pattern recognition, and medical imaging. The deep learning approach has opened new opportunities that can make such real-life applications and tasks easier and more efficient. The Handbook of Research on Deep Learning Innovations and Trends is an essential scholarly resource that presents current trends and the latest research on deep learning and explores the concepts, algorithms, and techniques of data mining and analysis. Highlighting topics such as computer vision, encryption systems, and biometrics, this book is ideal for researchers, practitioners, industry professionals, students, and academicians.

Aboul Ella Hassanien (Abo) is a Professor at Cairo University, Faculty of Computers and Information, IT Department and the Chair of Scientific Research Group in Egypt (SRGE). Abo is the chair of the International Rough Sets Society-Egypt Chapter. He received his BSc with honors in 1986 and MSc degree in 1993, both from Ain Shams University, Faculty of Science, Pure Mathematics and Computer Science Department, Cairo, Egypt. On September 1998, he received his doctoral degree from the Department of Computer Science, Graduate School of Science & Engineering, Tokyo Institute of Technology, Japan. He works in a multidisciplinary environment involving machine intelligence, network security and cryptology, data mining, various issues in intelligent environment including monitoring pollutions, technologies for disabled people including text-to-speech for blind people, Arabic sign Language, Social networks, biomedical engineering and bioinformatics and their applications to various real-world problems. He has authored/coauthored over 360 research publications in peer-reviewed reputed journals, book chapters and conference proceedings. He has served as the program committee member of various international conferences and reviewer for various international journals. He has received the excellence younger researcher award from Kuwait University for the academic year 2003/2004. He has guest edited many special issues for international scientific journals. He has directed many funded research projects. He is the editor and co-editor for more than 30 books in the area of rough computing, computational intelligence, social networks, bioinformatics, and E-commerce. For more details, please see http://www.egyptscience.net.

Chiranji Lal Chowdhary received his Ph.D. in information technology and engineering from VIT University; his M.Tech. in computer science and engineering from (M. S. Ramaiah Institute of Technology, Bangalore), Visvesvaraya Technological University, Belagavi; and his B.E. in computer science and engineering from MBM Engineering College, Jai Narain Vyas University, India. He is currently working as an Associate Professor in the School of Information Technology and Engineering, VIT University. He has 15 years of experience in academia and 6 months of experience in the industry. He has received research awards for publishing research papers in refereed journals from VIT University 5 times consecutively. He has guided more than 20 graduate projects and more than 20 postgraduate level projects. His publications are indexed by the Clarivate Analytics, IEEE Computer Society, SCOPUS, the ACM Digital Library, and other abstract and citation databases. He is a reviewer for many reputed journals. He is a life member of the Computer Society of India, the Indian Science Congress Association, and the Indian Society for Technical Education. He has published many papers in refereed journals and has attended international conferences. He has contributed many chapters and is currently in the process of editing books. He has written 3 books and editing 3 books with a reputed publisher. His current research included digital image processing, deep learning, pattern recognition, soft computing, and biometric systems.