Please note: In order to keep Hive up to date and provide users with the best features, we are no longer able to fully support Internet Explorer. The site is still available to you, however some sections of the site may appear broken. We would encourage you to move to a more modern browser like Firefox, Edge or Chrome in order to experience the site fully.

Supporting your high street Find out how »
A Guide to Convolutional Neural Networks for Computer Vision, Paperback / softback Book

A Guide to Convolutional Neural Networks for Computer Vision Paperback / softback

Part of the Synthesis Lectures on Computer Vision series

Paperback / softback

Item not Available

Description

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.

Information

Other Formats

£81.50

Item not Available
Item not Available
Sign in to add to wishlist
 
Free Home Delivery

on all orders

 
Pick up orders

from local bookshops

Information

Also in the Synthesis Lectures on Computer Vision series

Video Object Segmentation

£34.99

£31.89

Add to Basket

Video Object Tracking

£34.99

£31.89

Add to Basket

Visual Domain Adaptation in the Deep...

£77.00

Add to Basket