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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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## MobileNet-v2: Image Classification |
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MobileNet-v2 is an efficient deep convolutional neural network designed for mobile and embedded devices. It improves upon MobileNet-v1 by introducing an inverted residual structure and a linear bottleneck design. The inverted residuals enable efficient computation by retaining low-dimensional features, while the linear bottleneck reduces the transmission of redundant information, lowering computational costs. MobileNet-v2 achieves significant reductions in model parameters and computational overhead without sacrificing accuracy, making it suitable for environments with limited resources. It is widely used in tasks such as image classification, object detection, and semantic segmentation. |
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### Source model |
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- Input shape: 224x224 |
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- Number of parameters: 3.34M |
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- Model size: 13.34M |
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- Output shape: 1x1000 |
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Source model repository: [MobileNet-v2](https://github.com/pytorch/vision/blob/main/torchvision/models/mobilenetv2.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: [APACHE-2.0](https://github.com/tonylins/pytorch-mobilenet-v2/blob/master/LICENSE) |
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- Deployable Model: [APLUX-MODEL-FARM-LICENSE](https://aiot.aidlux.com/api/v1/files/license/model_farm_license_en.pdf) |
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