Author Description

Soft computing techniques have the ability to handle complex, uncertain, and imprecise information to create usable solutions to convoluted problems or those just too time-consuming to solve with current hardware. This new book details the use and applications of soft computing technology in several fields. Applied Soft Computing Techniques: Theoretical Principles and Practical Applications is strategically arranged into five sections to explore the use of these techniques in biomedical applications, communication technologies, data analytics and applications, image processing, and natural language processing. The chapters in the section on biomedical applications explore soft computing techniques for cancer data analysis, depression and mental health analysis, heart disease detection, etc. The editors go on to discuss soft computing in communication systems, looking at graphs, design processes, and mapping techniques, as well as the integration of IoT devices, drone technology, etc. The volume also details how soft computing methodologies can assist in tackling the obstacles associated with signal processing, network optimization, quality of service, and beyond. Several chapters discuss the use of soft computing techniques in data compression, handling of large-scaled heterogenous databases, visualization techniques, etc. Applications of soft computing in image processing are also discussed and cover human face recognition, casualty detection, traffic sign recognition, and predicting soil features using satellite imagery. Soft computing techniques in natural language processing consider text-to-speech signal conversion, NLP and speech recognition, speech emotion recognition, and more. This volume will help to facilitate the amalgamation of theoretical principles and practical applications, bringing forth possible solutions to complex problems in various domains. The book is a welcome resource for researchers, students, professionals,