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How to test Computer Vision Systems - Two Part Blog
In this two part blog, we want to explore how to test a Computer Vision system. We will do a deep dive into the process and best practices for properly and accurately run a computer vision test. The first part here will cover Annotation. Data annotation helps provide valuable insight and information with respect to the system requirements.The second part will cover evaluation and explain topics like accuracy, recall and precision.
Artificial Intelligence vs Machine Learning vs Deep Learning: How are they all connected?
Artificial Intelligence can thus be thought of as a system to help mimic human intelligence by using algorithms; techniques, rules and/or methods to learn, reason and react to different situations and scenarios like a human would do.
Sighthound IO: Deeply-Learned Computer Vision Technology Now on Windows
Companies needing to access computer vision through a cloud API have many choices.
Breaking Boundaries in License Plate Recognition
What would an ideal LPR system look like? Automated reading of license plates has been around for decades. Unfortunately, most of the technology has not changed much in that time.
Recognition of European Vehicles
Every year in the UK hundreds gather for the Festival of the Unexceptional. In usually damp surroundings the most unglamorous vehicles of a little-gilded age joust for the prize of most mediocre…