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--- |
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license: other |
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license_name: aplux-model-farm-license |
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license_link: https://aiot.aidlux.com/api/v1/files/license/model_farm_license_en.pdf |
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pipeline_tag: image-classification |
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tags: |
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- AIoT |
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- QNN |
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--- |
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## EfficientNet-B0: Image Classification |
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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. |
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### Source model |
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- Input shape: 224x224 |
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- Number of parameters: 5.04M |
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- Model size: 20.16M |
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- Output shape: 1x1000 |
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Source model repository: [EfficientNet-B0](https://github.com/pytorch/vision/blob/main/torchvision/models/efficientnet.py) |
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## Performance Reference |
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Please search model by model name in [Model Farm](https://aiot.aidlux.com/en/models) |
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## Inference & Model Conversion |
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Please search model by model name in [Model Farm](https://aiot.aidlux.com/en/models) |
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## License |
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- Source Model: [BSD-3-CLAUSE](https://github.com/pytorch/vision/blob/main/LICENSE) |
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- Deployable Model: [APLUX-MODEL-FARM-LICENSE](https://aiot.aidlux.com/api/v1/files/license/model_farm_license_en.pdf) |
