Extensive coverage of deep learning algorithms for diverse applications enables readers to grasp a wide range of techniques
Covers algorithms for imaging, seismic tomography, smart grids, surveillance, security, and healthcare to provide practical knowledge
Systematic discussions on development, evaluation, and relevance of algorithms offer in-depth understanding
Insights into fundamental design strategies for deep learning algorithms enhance reader expertise
Real-world case studies demonstrate the practical deployment of deep learning solutions
Summarized by Shop
Studies in Computational Intelligence Pedrycz, Witold; Chen, Shyi-Ming 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