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Computer Vision and Recognition Systems Using Machine and Deep Learning Approaches: Fundamentals, technologies and applications

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Editors: Chiranji Lal Chowdhary 1 ; Mamoun Alazab 2 ; Ankit Chaudhary 3 ; Saqib Hakak 4 ; Thippa Reddy Gadekallu 1
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Publication Year: 2021

Computer vision is an interdisciplinary scientific field that deals with how computers obtain, store, interpret and understand digital images or videos using artificial intelligence based on neural networks, machine learning and deep learning methodologies. They are used in countless applications such as image retrieval and classification, driving and transport monitoring, medical diagnostics and aerial monitoring. Written by a team of international experts, this edited book covers the state-of-the-art of advanced research in the fields of computer vision and recognition systems from fundamental concepts to methodologies and technologies and real world applications including object detection, biometrics, Deepfake detection, sentiment and emotion analysis, traffic enforcement camera monitoring, vehicle control and aerial remote sensing imagery. The book will be useful for industry and academic researchers, scientists and engineers in the fields of computer vision, machine vision, image processing and recognition, multimedia, AI, machine and deep learning, data science, biometrics, security, and signal processing. It will also make a great course reference for advanced students and lecturers in these fields of research.

Inspec keywords: image classification; learning (artificial intelligence); computer vision; convolutional neural nets; feature extraction

Other keywords: learning (artificial intelligence); convolutional neural nets; image classification; mobile computing; computer vision; support vector machines; driver information systems; object detection; feature extraction; deep learning (artificial intelligence)

Subjects: Computer vision and image processing techniques; General electrical engineering topics; General and management topics; Traffic engineering computing; Education and training; Neural nets; Optical, image and video signal processing

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