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Название: Intelligent Systems: Advances in Biometric Systems, Soft Computing, Image Processing, and Data Analytics
Автор: Chiranji Lal Chowdhary
Издательство: Apple Academic Press
Год: 2019
Страниц: 320
Язык: английский
Формат: pdf (true)
Размер: 10.4 MB

This volume helps to fill the gap between data analytics, image processing, and soft computing practices. Soft computing methods are used to focus on data analytics and image processing to develop good intelligent systems. To this end, readers of this volume will find quality research that presents the current trends, advanced methods, and hybridized techniques relating to data analytics and intelligent systems. The book also features case studies related to medical diagnosis with the use of image processing and soft computing algorithms in particular models.

This volume provides extensive coverage of biometric systems, soft computing, image processing, Artificial Intelligence (AI), and data analytics, the chapter authors discuss the latest research issues, present solutions to research problems, and look at comparative analysis with earlier results. Topics include some of the most important challenges and discoveries in intelligent systems today, such as computer vision concepts and image identification, data analysis and computational paradigms, Deep Learning techniques, face and speaker recognition systems, and more.

One of the fundamental problems of computer vision is the description of any sensory data. For example, sensory data are texture, shape, color, motion, weight, smell, touch, sound, etc. Using computer vision concepts, we require an approach to descriptions of the type of objects that we may recognize as baby, lion, toy, pet, horse, or dog. However, 2D object-recognition techniques are sensitive to illumination, shadows, scale, pose, and occlusions. 3D object recognition, on the other hand, does not suffer from these limitations. 3D information of the scene from a particular point of view can be computed with the use of depth maps. These motivated us to move to 3D object recognition.

Soft computing has been an important research area where data analysis is concerned. It was developed as a significant analysis and computing tool to facilitate biological and linguistic inspiration for computational paradigms by highlighting fuzzy systems, artificial neural networks, rough sets, learning systems, genetic algorithms, and hybrid systems. For real-life problems and decision-making, researchers and experts require computational intelligence tools for appropriate planning and operation
and for achieving proper results.

Contents:


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