Granular Video Computing: With Rough Sets, Deep Learning And In Iot (Hardcover)

This volume links the concept of granular computing using deep learning and the Internet of Things to object tracking for video analysis. It describes how uncertainties, involved in the task of video processing, could be handled in rough set theoretic granular computing frameworks. Issues such as object tracking from videos in constrained situations, occlusion/overlapping handling, measuring of the reliability of tracking methods, object recognition and linguistic interpretation in video scenes, and event prediction from videos, are the addressed in this volume. The book also looks at ways to reduce data dependency in the context of unsupervised (without manual interaction/ labeled data/ prior information) training.This book may be used both as a textbook and reference book for graduate students and researchers in computer science, electrical engineering, system science, data science, and information technology, and is recommended for both students and practitioners working in computer vision, machine learning, video analytics, image analytics, artificial intelligence, system design, rough set theory, granular computing, and soft computing.

General

Imprint:	World Scientific Publishing Co Pte Ltd
Country of origin:	Singapore
Release date:	February 2021
First published:	2021
Authors:	Debarati Bhunia Chakraborty • Sankar Kumar Pal
Dimensions:	159 x 236 x 22mm (L x W x T)
Format:	Hardcover
Pages:	256
ISBN-13:	978-981-12-2711-0
Categories:	Books > Computing & IT > Applications of computing > Artificial intelligence > Neural networks
LSN:	981-12-2711-X
Barcode:	9789811227110

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