Название: Granular Video Computing: With Rough Sets, Deep Learning And In IotАвтор: Debarati Bhunia Chakraborty, Sankar Kumar Pal
Издательство: World Scientific
Год: 2021
Страниц: 256
Язык: английский
Формат: pdf (true), epub
Размер: 52.12 MB, 10.1 MB
This volume links the concept of granular computing using Deep Learning (DL) and the Internet of Things (IoT) 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.
Deep learning architecture is a popular tool in the problem of object recognition. The task of labeling different objects in an image with the correct class and predicting the bounding boxes along with probability are done with this network. While deep learning is a computationally intensive process, and the aforesaid granular computing paradigm, on the other hand, leads to gain in computation time, it may be appropriate and logical to make their judicious integration so as to make the deep learning framework efficient in terms of computation time.
The book is unique in its character, and will be useful to graduate students and researchers in computer science, electrical engineering, system science, data science and information technology, both as a textbook and a reference book for some parts of the curriculum. The researchers and practitioners in industry and R&D laboratories working in the fields of system design, pattern recognition, machine learning, deep neural networks, Big data analytics, video surveillance, IoT and soft computing or computational intelligence will also be benefited.
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