[Solved] ECE495-Assignment 4 Object Detection with SSD
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- Continue gaining experience with PyTorch and helper libraries
- Understand the VOC Object Detection Dataset
- Train and evaluate the SSD neural network architecture
- Perform an ablation study testing a different base network and learning rate schedule
- Learn the Non-Maximum Suppression (NMS) algorithm
- Create a folder called ece495_assignment4 within your Google Colab Colab Notebooks folder.
- Upload the assignment ipynb, utils.py and json files to the Google Colab ece495_assignment4 folder
- Open the assignment
- Runtime -> change runtime type
- Set hardware accelerator to GPU
- Ablation study on using a different network base
- Model A: Train and evaluate the SSD network with the default VGG base.
- Model B: Implement the ResNetBase class. Then train and evaluate this model.
- Ablation study on updating the learning rate
- Model C: Train and evaluate the SSD network with the default VGG base but also with a PyTorch learning rate scheduler.
- Answer 2 questions on the differences from the NMS pseudo code described in the lectures / tutorial and the implemented version in the code.