Introduction to Track C
Track C is for members to learn the vision part of Artificial Intelligence, such as object classification, object detection, object segmentation, pose estimation, and scene understanding. The objective of the track is to enable members with the basic Deep Learning knowledge to develop modern vision solutions with Artificial Intelligence. Computer Vision is used in a broad range of applications, for instance, autonomous driving, medical diagnosis, plant disease prediction, product fault detection, etc.
Prerequisites
The basic knowledge of Deep Learning is required to understand Computer Vision.
Main Contents
The members will learn the following knowledge and skills in this track:
Fundamentals of Computer Vision
Computer Vision Tasks and Applications
R-CNN and Applications
Mask R-CNN and Applications
YOLO and Applications
SSD and Applications
R-FCN and Applications
The Latest Developments and Algorithms in Computer Vision