Learn Computer Vision Using OpenCV: With Deep Learning CNNs and RNNs By Sunila Gollapudi PDF - Zeldatech

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Tuesday, 29 October 2019

Learn Computer Vision Using OpenCV: With Deep Learning CNNs and RNNs By Sunila Gollapudi PDF

Download Book : Learn Computer Vision Using OpenCV: With Deep Learning CNNs and RNNs By Sunila Gollapudi PDF




Informations about the book:


TitleLearn Computer Vision Using OpenCV: With Deep Learning CNNs and RNNs

AuthorSunila Gollapudi 

Size: 6.3 MB

Format: PDF

Year: 2019

Pages: -


Book Contents:


Chapter 1: Artificial Intelligence and Computer Vision
Introduction to Artificial Intelligence
Introduction to Computer Vision
Chapter 2: OpenCV with Python
About OpenCV
Setting Up OpenCV with Python
Using Modules
Working with Images and Videos
Chapter 3: Deep Learning for Computer Vision
Deep Learning: An Overview
Deep Learning Applications in Computer Vision
Image Captioning
Generative Models
Video Analysis
Neural Networks at Their Core
Convolutional Neural Networks
Recurrent Neural Networks
Chapter 4: Image Manipulation and Segmentation
Image Manipulations
Image Segmentation
Chapter 5: Object Detection and Recognition
Basics of Object Detection
Feature Matching
Chapter 6: Motion Analysis and Object Tracking
Introduction to Object Tracking
Challenges of Object Tracking
Object Detection Techniques for Tracking
Object Classification
Object Tracking Methods


Description:


This book starts with setting up OpenCV with Python from scratch and
then covers implementing specialized image processing, implementing
object/feature detection and motion tracking functions, using advanced
libraries, and productionizing large-scale deployments using OpenCV.
The high-level objectives of the book are as follows:

• Understand what computer vision is and its overall
application in AI and intelligent automation systems

• Learn all the deep learning techniques required and
used for building computer vision applications

• Learn how to build complex computer vision
applications using the latest techniques in OpenCV
using programming skills such as basic Python and
NumPy

• See practical applications and implementations such
as face detection and recognition (face swapping and
filters!), handwriting recognition, object detection,
tracking, and motion analysis


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