A Guide to Convolutional Neural Networks for Computer Vision

Salman Khan, Hossein Rahmani, Syed Afaq Ali Shah, Mohammed Bennamoun

Research output: Book/ReportBook

Abstract

Computer vision has become increasingly important and effective in recent years due to its wide-ranging applications in areas as diverse as smart surveillance and monitoring, health and medicine, sports and recreation, robotics, drones, and self-driving cars. Visual recognition tasks, such as image classification, localization, and detection, are the core building blocks of many of these applications, and recent developments in Convolutional Neural Networks (CNNs) have led to outstanding performance in these state-of-the-art visual recognition tasks and systems. As a result, CNNs now form the crux of deep learning algorithms in computer vision.

This self-contained guide will benefit those who seek to both understand the theory behind CNNs and to gain hands-on experience on the application of CNNs in computer vision. It provides a comprehensive introduction to CNNs starting with the essential concepts behind neural networks: training, regularization, and optimization of CNNs. The book also discusses a wide range of loss functions, network layers, and popular CNN architectures, reviews the different techniques for the evaluation of CNNs, and presents some popular CNN tools and libraries that are commonly used in computer vision. Further, this text describes and discusses case studies that are related to the application of CNN in computer vision, including image classification, object detection, semantic segmentation, scene understanding, and image generation.

This book is ideal for undergraduate and graduate students, as no prior background knowledge in the field is required to follow the material, as well as new researchers, developers, engineers, and practitioners who are interested in gaining a quick understanding of CNN models.
Original languageEnglish
PublisherMorgan & Claypool Publishers
Number of pages207
DOIs
Publication statusPublished - 2018

Publication series

NameSynthesis Lectures on Computer Vision
No.1
Volume8
ISSN (Print)2153-1056
ISSN (Electronic)2153-1064

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Computer vision
Neural networks
Image classification
Sports medicine
Network layers
Network architecture
Learning algorithms
Robotics
Railroad cars
Semantics
Health
Students
Engineers
Monitoring

Cite this

Khan, S., Rahmani, H., Shah, S. A. A., & Bennamoun, M. (2018). A Guide to Convolutional Neural Networks for Computer Vision. (Synthesis Lectures on Computer Vision; Vol. 8, No. 1). Morgan & Claypool Publishers. https://doi.org/10.2200/S00822ED1V01Y201712COV015
Khan, Salman ; Rahmani, Hossein ; Shah, Syed Afaq Ali ; Bennamoun, Mohammed. / A Guide to Convolutional Neural Networks for Computer Vision. Morgan & Claypool Publishers, 2018. 207 p. (Synthesis Lectures on Computer Vision; 1).
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Khan, S, Rahmani, H, Shah, SAA & Bennamoun, M 2018, A Guide to Convolutional Neural Networks for Computer Vision. Synthesis Lectures on Computer Vision, no. 1, vol. 8, Morgan & Claypool Publishers. https://doi.org/10.2200/S00822ED1V01Y201712COV015

A Guide to Convolutional Neural Networks for Computer Vision. / Khan, Salman ; Rahmani, Hossein; Shah, Syed Afaq Ali; Bennamoun, Mohammed.

Morgan & Claypool Publishers, 2018. 207 p. (Synthesis Lectures on Computer Vision; Vol. 8, No. 1).

Research output: Book/ReportBook

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