Neural Network Computer Vision with OpenCV 5

Neural Network Computer Vision with OpenCV equips you with professional skills and knowledge to build intelligent vision systems using OpenCV. It creates a sequential pathway for understanding morphological operations, edge and corner detection, object localization, image classification, segmentation, and advanced applications like face detection and recognition, and optical character recognition. 

This book offers a practical roadmap to explore the nuances of image processing with detailed discussions on each topic, supported by hands-on Python code examples. The readers will learn the basics of neural networks, deep learning and CNNs by using deep learning frameworks like Keras, Tensorflow, PyTorch, Caffe etc. They will be able to utilize OpenCV DNN module to classify images by using  models like Inception V3, Resnet 101, Mobilenet V2. Moreover, the book will help to successfully Implement object detection using YOLOv3, SSD and R-CNN models. The character detection and recognition models are also covered in depth with code examples.

You will gain a deeper understanding of how these techniques impact real-world scenarios and learn to harness the potential of Python and OpenCV to solve complex problems. Whether you are building intelligent systems, automating processes, or working on image-related projects, this book equips you with the skills to revolutionize your approach to visual data.

KEY FEATURES  

• Practical solutions to image processing challenges.
• Detect and classify objects in images.
• Recognize faces and text from images using character detection and recognition models.

WHAT YOU WILL LEARN

• Acquire expertise in image manipulation techniques.
• Apply knowledge to practical scenarios in computer vision.
• Implement robust systems for face detection and recognition.
• Enhance projects with accurate object localization capabilities.
• Extract text information from images effectively.

WHO THIS BOOK IS FOR

This book is designed for those with basic Python skills, from beginners to intermediate-level readers. Whether you are building intelligent robots that perceive their surroundings or crafting advanced vision systems for object detection and image analysis, this book will equip you with the tools and skills to push the boundaries of AI perception.

1. Introduction to Computer Vision
2. Basics of Imaging
3. Challenges in Computer Vision
4. Classical Solutions
5. Deep Learning and CNNs
6. OpenCV DNN Module
7. Modern Solutions for Image Classification
8. Modern Solutions for Object Detection
9. Faces and Text
10. Running the Code
11. End-to-end Demo

Gopi Krishna Nuti is an experienced professional with 21 years of experience in IT industry. He has done his B. Tech in Computer Science from Andhra University, M.S in Business Analytics from State University of New York at Buffalo and an Executive MBA from Amrita University, Bengaluru. He has worked extensively in analytics and software development projects and has delivered award winning products and solutions. He has authored a book about Machine Learning and has multiple patents and research papers against his name. He is a faculty at various training events and a guest faculty at various Engineering Colleges in AP and Telangana. He is a member of the board of studies for Geetanjali Institute of Science and Technology. He is currently working as a Data Science Manager at Autodesk, Bengaluru. He also volunteers for MUST Research and is committed to democratizing AI for al. An incorrigible foodie, he is a passionate teacher and is obsessed with demystifying AI for the next generation of Software developers.