EfficientNet-B0 / README.md
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metadata
license: other
license_name: aplux-model-farm-license
license_link: https://aiot.aidlux.com/api/v1/files/license/model_farm_license_en.pdf
pipeline_tag: image-classification
tags:
  - AIoT
  - QNN

EfficientNet-B0: Image Classification

EfficientNet-B0 is the baseline model in the EfficientNet series introduced by Google in 2019. EfficientNet employs a "compound scaling" method, which jointly optimizes the network's depth, width, and resolution to achieve greater computational efficiency and accuracy. EfficientNet-B0 utilizes the Mobile Inverted Bottleneck Convolution (MBConv) module along with depthwise separable convolutions, significantly reducing parameters and computational cost. Despite being the smallest model in the series, EfficientNet-B0 performs excellently across various computer vision tasks, delivering high accuracy while maintaining low resource requirements, making it ideal for mobile devices and edge computing in resource-constrained environments.

Source model

  • Input shape: 224x224
  • Number of parameters: 5.04M
  • Model size: 20.16M
  • Output shape: 1x1000

Source model repository: EfficientNet-B0

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