Computer Vision

Create image processing, object detection and face recognition apps by leveraging the power of machine learning and deep learning with OpenCV 4 and Qt 5

A practical guide designed to get you from basics to current state of art in computer vision systems.

Turn futuristic ideas about computer vision and machine learning into demonstrations that are both functional and entertaining

Discover interesting recipes to help you understand the concepts of object detection, image processing, and facial detection

Recipe-based approach to tackle the most common problems in Computer Vision by leveraging the functionality of OpenCV using Python APIs

Create advanced applications with Python and OpenCV, exploring the potential of facial recognition, machine learning, deep learning, web computing and augmented reality.

Work on practical computer vision projects covering advanced object detector techniques and modern deep learning and machine learning algorithms

A practical guide to understanding the core machine learning and deep learning algorithms, and implementing them to create intelligent image processing systems using OpenCV 4

Discover how CUDA allows OpenCV to handle complex and rapidly growing image data processing in computer and machine vision by accessing the power of GPU

A practical guide to building high performance systems for object detection, segmentation, video processing, smartphone applications, and more

Explore the various packages in Julia that support image processing and build neural networks for video processing and object tracking

Create powerful, accurate, and real-time Computer Vision applications using a perfect blend of algorithms and filters. Also learn about object tracking and foreground extractions with a variety of new filters and algorithms.