عنوان

A guide to convolutional neural networks for computer vision

(Number (ISBN

9781681730219 (pbk)

(Number (ISBN

9781681730226 (ebook)

Number

2069

.Language of Text, Soundtrack etc

انگلیسی

Title Proper

A guide to convolutional neural networks for computer vision

General Material Designation

[electronic resources]

First Statement of Responsibility

/ Salman Khan... [et al.].

Place of Publication, Distribution, etc.

[San Rafael, California]

Name of Publisher, Distributor, etc.

: Morgan & Claypool

Date of Publication, Distribution, etc.

, 2018.

Specific Material Designation and Extent of Item

184 pages.

Other Physical Details

: illustrations (color).

Series Title

Synthesis lectures on computer vision, # 15

Text of Note

Authors: Salman Khan, Hossein Rahmani, Syed Afaq Ali Shah, M Bennamoun.

Text of Note

Bibliographical references pages [173]-184.

Text of Note

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.

Entry Element

Computer vision -- Mathematical models.

Entry Element

Neural networks (Computer science).

Subject Term

Neural networks, Computer vision, Mathematical models, Computer science.

Relator Code

Author

Khan, Salman,

Country

ایران

Agency

Central Library of the Kurdistan University

e

BL

280328

a

Y