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.
Salman Khan A Guide to Convolutional Neural Networks for Computer Vision (Synthesis Lectures on Computer Vision) free
A Guide to Convolutional Neural Networks for Computer Vision (Synthesis Lectures on Computer Vision) pdf download
A Guide to Convolutional Neural Networks for Computer Vision (Synthesis Lectures on Computer Vision) free ebook pdf epub
No comments:
Post a Comment
Note: Only a member of this blog may post a comment.