Название: Applied Computer Vision and Soft Computing with Interpretable AI
Автор: Swati V. Shinde, Darshan V. Medhane, Oscar Castillo
Издательство: CRC Press
Год: 2023
Страниц: 333
Язык: английский
Формат: pdf (true)
Размер: 41.0 MB

This reference text presents the knowledge base of computer vision and soft computing techniques with their applications for sustainable developments.

Computer Vision is the field of studying and developing technology that enables computers to process, analyze, and interpret digital images. Today, Computer Vision applications can be found in several industries, such as industrial robots, medical imaging, and surveillance. On the other hand, soft computing is being used to reduce the limitations caused by problems in data analytics. Moreover, soft computing is emerging as an innovative technological approach with the ability to allow a broad range of applications which can transform human lives in excellent ways.

The diverse perspectives of soft computing involve numerous aspects of interpretable Artificial Intelligence. Interpretable artificial intelligence incorporates theories, concepts, and techniques of science, internet technology, computer technology, neuroscience, and so on in a highly multidisciplinary way. It also offers a high computational dynamism. In view of the importance of an interpretable artificial intelligence as an emerging trend and technological approach to be followed in multidisciplinary research areas, we are pleased to present a book titled Applied Computer Vision and Soft Computing with Interpretable AI.

Researchers and practitioners have contributed to this book by means of chapters that illustrate research results, projects, surveying works, and industrial experiences that describe significant advances in the areas of computer vision, soft computing, and interpretable Artificial Intelligence. This book is organized in 20 chapters.

It is intended to be a major reference tool for scientists and engineers interested in applying new
computational and mathematical concepts to design applications based on interpretable AI.

Features:

∙ Covers a variety of deep learning architectures useful for computer vision tasks.

∙ Demonstrates the use of different soft computing techniques and their applications for different computer vision tasks.

∙ Highlights the unified strengths of hybrid techniques based on deep learning and soft computing taken together that give the interpretable, adaptive, and optimized solution to a given problem.

∙ Addresses the different issues and further research opportunities in computer vision and soft computing.

∙ Describes all the concepts with practical examples and case studies with appropriate performance measures that validate the applicability of the respective technique to a certain domain.

∙ Considers recent real word problems and the prospective solutions to these problems.

This book will be useful to researchers, students, faculty, and industry personnel who are eager to explore the power of deep learning and soft computing for different computer vision tasks.