a-PyTorch-Tutorial-to-Object-Detection
This tutorial guides on constructing object detection models with PyTorch, beginning with essential concepts in PyTorch and convolutional networks. It explains the SSD implementation, covering crucial elements like Multiscale Feature Maps and Priors, while offering insights into its architecture. Discover methods to improve model efficiency, such as Hard Negative Mining and Non-Maximum Suppression. Enhanced with practical examples and annotated images, this guide highlights model structure comprehension and prediction optimization.