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Big Data subsumes many types of data analytic approaches, while Video Analytics generally means computer vision and image analysis on video.

Intelligent image processing using deep learning is everywhere.

The U-Net approach allows data‑driven models to automatically learn robust feature representations to generate state-of-the-art results.

The rapid expansion of computer-vision-based systems and applications is enabled by many factors.

A book, according to Jon Peddie, that everyone interested in big data and visualization should read.

People tracking can be seen as a subset of either object tracking or skeletal tracking, depending on the end goal of the tracking system.

An open software ecosystem is critical to enable developers to write AI software that takes full advantage of the latest processors.

Computer vision at the edge need to deal deal with distorted images from wide-angle lenses, image stabilization, low-light conditions, etc.

In recent years, visual effects in movies and television have grown both more sophisticated and more ubiquitous.

Intel began the Computer Vision Annotation Tool project a few years ago in order to speed up the annotation of digital images and videos.