In the paper "ForestNet: Classifying Drivers of Deforestation in Indonesia using Deep Learning on Satellite Imagery", the authors talk about using:
- Feature Pyramid Networks (as the architecture)
- EfficientNet-B2 (as the backbone)
What's the difference between architectures and backbones? I can't find much online. Specifically, what are their respective purposes? From a high-level perspective, what would integrating the two look like?