CV/LIDAR deep learning
The goal for CV deep learning is to implement deep learning models to accurately assign various classifications to objects detected by our boat’s ZED camera. These models will replace our current classical CV detection system, which is slow and unstable. Upon completion, this new detection method will be integrated into our boat’s architecture, along with the development of a streamlined process for creating and training new models. Members will gain hands-on experience with one or more steps of the deep learning process, including model selection, design, training, and validation, as well as data annotation and preprocessing. Additionally, members may optionally also seek to gain a more theoretical understanding of deep learning models (and by extension, machine learning as a whole).