Here at Hasty.ai, we work on visionAI projects daily. Too often, our team was looking for a visionAI wiki where the most relevant terms around visionAI are explained in a condensed way. So often, that we decided to start it our own.
We're just getting started, so a lot of things are still missing. But over time, this will be a comprehensive resource for everyone working on practical visionAI problems. You can help to make this happen.
As the name suggests, the wiki is all-around visionAI. It explains the most relevant concepts and tries to cover each's practical implications. The goal is not to explain every theoretical detail of the ideas presented but to give the reader all information needed so that he/she can apply it to their project.
All terms contain a description, including a brief explanation, some context on how to apply the concept in practice, links for further theoretical understanding, and if applicable, a code example for the implementation.
Check our overview to see what topics are covered specifically.
Hopefully, the wiki will be helpful for:
Newbies who are just getting started and looking for explanations and useful resources for terms they stumble across during their work;
Experts who want to refresh their knowledge on a certain topic;
Teams who are talking about the same concepts but using different terms for it and are looking for ground truth for their terminology use (that's us, by the way).
However, the wiki is not intended for people who are starting at zero. For these persons, we recommend the introductory lecture series to computer vision by Joseph Redmon. After watching all videos, the wiki can be used to navigate you through the world of visionAI.