This book presents a wealth of deep-learning algorithms and demonstrates their design process. It also highlights the need for a prudent alignment with the essential characteristics of the nature of learning encountered in the practical problems being tackled. Intended for readers interested in acquiring practical knowledge of analysis, design, and deployment of deep learning solutions to real-world problems, it covers a wide range of the paradigm’s algorithms and their applications in diverse areas including imaging, seismic tomography, smart grids, surveillance and security, and health care, among others. Featuring systematic and comprehensive discussions on the development processes, their evaluation, and relevance, the book offers insights into fundamental design strategies for algorithms of deep learning.
Author(s): Witold Pedrycz, Shyi-Ming Chen
Series: Studies In Computational Intelligence
Publisher: Springer
Year: 2020
Language: English
Pages: 368
Tags: Computational Intelligence, Deep Learning
Front Matter ....Pages i-xii
Activation Functions (Mohit Goyal, Rajan Goyal, P. Venkatappa Reddy, Brejesh Lall)....Pages 1-30
Adversarial Examples in Deep Neural Networks: An Overview (Emilio Rafael Balda, Arash Behboodi, Rudolf Mathar)....Pages 31-65
Representation Learning in Power Time Series Forecasting (Janosch Henze, Jens Schreiber, Bernhard Sick)....Pages 67-101
Deep Learning Application: Load Forecasting in Big Data of Smart Grids (Abdulaziz Almalaq, Jun Jason Zhang)....Pages 103-128
Fast and Accurate Seismic Tomography via Deep Learning (Mauricio Araya-Polo, Amir Adler, Stuart Farris, Joseph Jennings)....Pages 129-156
Traffic Light and Vehicle Signal Recognition with High Dynamic Range Imaging and Deep Learning (Jian-Gang Wang, Lu-Bing Zhou)....Pages 157-192
The Application of Deep Learning in Marine Sciences (Miguel Martin-Abadal, Ana Ruiz-Frau, Hilmar Hinz, Yolanda Gonzalez-Cid)....Pages 193-230
Deep Learning Case Study on Imbalanced Training Data for Automatic Bird Identification (Juha Niemi, Juha T. Tanttu)....Pages 231-262
Deep Learning for Person Re-identification in Surveillance Videos (Swathi Jamjala Narayanan, Boominathan Perumal, Sangeetha Saman, Aditya Pratap Singh)....Pages 263-297
Deep Learning in Gait Analysis for Security and Healthcare (Omar Costilla-Reyes, Ruben Vera-Rodriguez, Abdullah S. Alharthi, Syed U. Yunas, Krikor B. Ozanyan)....Pages 299-334
Deep Learning for Building Occupancy Estimation Using Environmental Sensors (Zhenghua Chen, Chaoyang Jiang, Mustafa K. Masood, Yeng Chai Soh, Min Wu, Xiaoli Li)....Pages 335-357
Back Matter ....Pages 359-360
