A Compact Version of EfficientNet

Abstract

EfficientNet is a convolutional neural network architecture that was created by doing a neural architecture search with the AutoML MNAS framework, which optimized both accuracy and efficiency. It is based on MobileNetV2’s inverted bottleneck residual blocks, as well as squeeze-and-excite blocks. With far lower parameter computation burdens on the ImageNet challenge, EfficientNet may compete with the best. This paper provides a mobile version of EfficientNet that has accuracy similar to the ImageNet dataset but runs nearly twice as fast.