Share

A Guide to Convolutional Neural Networks for Computer Vision

2022-06-01 Computers
Download A Guide to Convolutional Neural Networks for Computer Vision PDF Online Free

Author :
Release : 2022-06-01
Genre : Computers
Kind : eBook
Book Rating : 214/5 ( reviews)

GET EBOOK


Book Synopsis A Guide to Convolutional Neural Networks for Computer Vision by : Salman Khan

Download or read book A Guide to Convolutional Neural Networks for Computer Vision written by Salman Khan. This book was released on 2022-06-01. Available in PDF, EPUB and Kindle. Book excerpt: 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.

A Guide to Convolutional Neural Networks for Computer Vision

2018-02-13 Computers
Download A Guide to Convolutional Neural Networks for Computer Vision PDF Online Free

Author :
Release : 2018-02-13
Genre : Computers
Kind : eBook
Book Rating : 219/5 ( reviews)

GET EBOOK


Book Synopsis A Guide to Convolutional Neural Networks for Computer Vision by : Salman Khan

Download or read book A Guide to Convolutional Neural Networks for Computer Vision written by Salman Khan. This book was released on 2018-02-13. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Convolutional Neural Networks In Python

2020-07-06 Computers
Download Convolutional Neural Networks In Python PDF Online Free

Author :
Release : 2020-07-06
Genre : Computers
Kind : eBook
Book Rating : /5 ( reviews)

GET EBOOK


Book Synopsis Convolutional Neural Networks In Python by : Frank Millstein

Download or read book Convolutional Neural Networks In Python written by Frank Millstein. This book was released on 2020-07-06. Available in PDF, EPUB and Kindle. Book excerpt: Convolutional Neural Networks in Python This book covers the basics behind Convolutional Neural Networks by introducing you to this complex world of deep learning and artificial neural networks in a simple and easy to understand way. It is perfect for any beginner out there looking forward to learning more about this machine learning field. This book is all about how to use convolutional neural networks for various image, object and other common classification problems in Python. Here, we also take a deeper look into various Keras layer used for building CNNs we take a look at different activation functions and much more, which will eventually lead you to creating highly accurate models able of performing great task results on various image classification, object classification and other problems. Therefore, at the end of the book, you will have a better insight into this world, thus you will be more than prepared to deal with more complex and challenging tasks on your own. Here Is a Preview of What You’ll Learn In This Book… Convolutional neural networks structure How convolutional neural networks actually work Convolutional neural networks applications The importance of convolution operator Different convolutional neural networks layers and their importance Arrangement of spatial parameters How and when to use stride and zero-padding Method of parameter sharing Matrix multiplication and its importance Pooling and dense layers Introducing non-linearity relu activation function How to train your convolutional neural network models using backpropagation How and why to apply dropout CNN model training process How to build a convolutional neural network Generating predictions and calculating loss functions How to train and evaluate your MNIST classifier How to build a simple image classification CNN And much, much more! Get this book NOW and learn more about Convolutional Neural Networks in Python!

Guide to Convolutional Neural Networks

2017-05-17 Computers
Download Guide to Convolutional Neural Networks PDF Online Free

Author :
Release : 2017-05-17
Genre : Computers
Kind : eBook
Book Rating : 503/5 ( reviews)

GET EBOOK


Book Synopsis Guide to Convolutional Neural Networks by : Hamed Habibi Aghdam

Download or read book Guide to Convolutional Neural Networks written by Hamed Habibi Aghdam. This book was released on 2017-05-17. Available in PDF, EPUB and Kindle. Book excerpt: This must-read text/reference introduces the fundamental concepts of convolutional neural networks (ConvNets), offering practical guidance on using libraries to implement ConvNets in applications of traffic sign detection and classification. The work presents techniques for optimizing the computational efficiency of ConvNets, as well as visualization techniques to better understand the underlying processes. The proposed models are also thoroughly evaluated from different perspectives, using exploratory and quantitative analysis. Topics and features: explains the fundamental concepts behind training linear classifiers and feature learning; discusses the wide range of loss functions for training binary and multi-class classifiers; illustrates how to derive ConvNets from fully connected neural networks, and reviews different techniques for evaluating neural networks; presents a practical library for implementing ConvNets, explaining how to use a Python interface for the library to create and assess neural networks; describes two real-world examples of the detection and classification of traffic signs using deep learning methods; examines a range of varied techniques for visualizing neural networks, using a Python interface; provides self-study exercises at the end of each chapter, in addition to a helpful glossary, with relevant Python scripts supplied at an associated website. This self-contained guide will benefit those who seek to both understand the theory behind deep learning, and to gain hands-on experience in implementing ConvNets in practice. As no prior background knowledge in the field is required to follow the material, the book is ideal for all students of computer vision and machine learning, and will also be of great interest to practitioners working on autonomous cars and advanced driver assistance systems.

Convolutional Neural Networks in Visual Computing

2017-10-23 Computers
Download Convolutional Neural Networks in Visual Computing PDF Online Free

Author :
Release : 2017-10-23
Genre : Computers
Kind : eBook
Book Rating : 327/5 ( reviews)

GET EBOOK


Book Synopsis Convolutional Neural Networks in Visual Computing by : Ragav Venkatesan

Download or read book Convolutional Neural Networks in Visual Computing written by Ragav Venkatesan. This book was released on 2017-10-23. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the fundamentals in designing and deploying techniques using deep architectures. It is intended to serve as a beginner's guide to engineers or students who want to have a quick start on learning and/or building deep learning systems. This book provides a good theoretical and practical understanding and a complete toolkit of basic information and knowledge required to understand and build convolutional neural networks (CNN) from scratch. The book focuses explicitly on convolutional neural networks, filtering out other material that co-occur in many deep learning books on CNN topics.

You may also like...