We will be discussing fundamental metrics used to evaluate and compare computer vision systems such as accuracy, recall and precision. We will cover evaluations of the two main branches of computer vision: classification and detection.

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 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.

Today Sighthound, Inc. launched a new suite of Automatic License Plate Recognition (ALPR) software, services, and solutions built on its 10-year heritage of innovative computer vision products…

Today we’re releasing Sighthound Video 6.0 for general availability. True to our commitment in April, Sighthound Video 6 is free for all users who purchased Sighthound Video after January 1st…

Today we release the first Release Candidate version for Sighthound Video. It improves upon the previous Beta 3 release, and introduces the following changes: Updating our support integration in…

Today we are excited to release Sighthound Video 6.0 Beta 2. Before I go into the list of changes, I would like to thank each and every one of our users who tried Beta 1, and especially those of…

Hello Sighthound Video Users -

Sighthound Video 6 (SV6) is now available as an open BETA! You can download it from the Sighthound account...

First, some history about me and Sighthound Video.

I've been a user of Vitamin-D (The original name of Sighthound Video) since 2010. Actually, I just found the first forum post I made…

Companies needing to access computer vision through a cloud API have many choices.

One of the things that Sighthound has historically done well is finding faces. So many customer use cases require us to find human faces that we’ve put a lot of research hours into it.

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.