We’ll discuss and compare different computer vision techniques, both AI/deep learning-driven and traditional, including methods and algorithms based on neural networks, linear regression, random forests, edge detection, and texture classification.
Then, you’ll get to explore and try some out for yourself using OpenCV, TensorFlow, and Google Colaboratory as you work together with other participants to try developing solutions for detecting a given object - against arbitrary backgrounds and from different perspectives - in a dataset of pictures we’ll provide.
No prior experience with AI specifically is needed, but you should have some prior general programming experience, ideally with Python.
These sessions are developed and presented by students, alumni, and mentors of FRC teams 254, 604, 1700, 1868, 2473, and 3501.
Host: Starfish Mission
Please note: Sessions 1 and 2, when offered, are independent of each other; they're offered twice just so more participants have chances to attend, so you only need to register for one.