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.
The wiki is hosted and mainly maintained by Hasty.ai. However, we believe that crowd-sourced knowledge is the best knowledge, so we'd be more than happy if you'd contribute to the wiki. If you're comfortable with disclosing your identity to us, please write an email to [email protected] and we send you a small thank you for contributing!
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:
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.
Only 13% of vision AI projects make it to production, with Hasty we boost that number to 100%.