Definition
Developed by Google, EfficientNet uses a compound scaling method to balance network depth, width, and input image resolution. This approach allows the model to achieve state-of-the-art accuracy while being significantly smaller and faster than previous architectures like ResNet. It is widely used in computer vision tasks where computational efficiency and memory constraints are important considerations.
Summary
EfficientNet is a family of convolutional neural network architectures that scales depth, width, and resolution uniformly to achieve higher accuracy with fewer parameters.
Key Concepts
- Compound scaling
- MobileNetV2 blocks
- SE attention
- Parameter efficiency
Use Cases
- Image classification on mobile devices
- Object detection in resource-constrained environments
- Feature extraction for large-scale visual datasets