What is compound scaling in EfficientNet?
hardAnswer
- Scale depth (d), width (w), and resolution (r) together by a single coefficient φ: d = α^φ, w = β^φ, r = γ^φ, with ≈ 2 to keep FLOPs proportional to 2^φ.
- Better than scaling one dimension at a time.
- Combined with a NAS-found base (EfficientNet-B0) and MBConv blocks (mobile inverted bottleneck), EfficientNet-B7 hit 84% ImageNet top-1 in 2019 at 8.4x fewer params than the previous SOTA.
Check yourself — multiple choice
- Scale only depth
- Jointly scale depth, width, and resolution with a compound coefficient — Pareto-optimal accuracy/FLOPs
- EfficientNet uses no NAS
- Only scales width
EfficientNet compound scaling: joint depth/width/resolution → Pareto-optimal.
#architectures#computer-vision
Practise Deep Learning
214 interview questions in this topic.