EfficientNetV2: Smaller Models and Faster Training A new p | Data Science by ODS.ai 🦜
EfficientNetV2: Smaller Models and Faster Training
A new paper from Google Brain with a new SOTA architecture called EfficientNetV2. The authors develop a new family of CNN models that are optimized both for accuracy and training speed. The main improvements are:
- an improved training-aware neural architecture search with new building blocks and ideas to jointly optimize training speed and parameter efficiency; - a new approach to progressive learning that adjusts regularization along with the image size;
As a result, the new approach can reach SOTA results while training faster (up to 11x) and smaller (up to 6.8x).
Paper: https://arxiv.org/abs/2104.00298
Code will be available here: https://github.com/google/automl/tree/master/efficientnetv2
A detailed unofficial overview of the paper: https://andlukyane.com/blog/paper-review-effnetv2
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