|
|
--- |
|
|
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 |
|
|
--- |
|
|
|
|
|
 |
|
|
|
|
|
## Inception-v3: Image Classification |
|
|
|
|
|
Inception-v3 is the third version of the Inception series proposed by Google, known for its efficiency in convolutional neural networks and widely used for image classification tasks. The key idea behind Inception-v3 is its modular design, where multiple convolution filters of different sizes run in parallel, enabling the extraction of multi-scale features to improve the network’s representational power. The model incorporates techniques like batch normalization, factorized convolutions, and auxiliary classifiers, which reduce computational complexity while enhancing stability and accuracy. Inception-v3 has demonstrated outstanding performance on the ImageNet classification task, making it a key benchmark in deep learning. |
|
|
|
|
|
### Source model |
|
|
|
|
|
- Input shape: 299x299 |
|
|
- Number of paramaters: 25.9M |
|
|
- Model size: 90.9M |
|
|
- Output shape: 1x1000 |
|
|
|
|
|
Source model repository: [Inception-v3](https://github.com/pytorch/vision/blob/main/torchvision/models/inception.py) |
|
|
|
|
|
## Performance Reference |
|
|
|
|
|
Please search model by model name in [Model Farm](https://aiot.aidlux.com/en/models) |
|
|
|
|
|
## Inference & Model Conversion |
|
|
|
|
|
Please search model by model name in [Model Farm](https://aiot.aidlux.com/en/models) |
|
|
|
|
|
## License |
|
|
|
|
|
- Source Model: [BSD-3-CLAUSE](https://github.com/pytorch/vision/blob/main/LICENSE) |
|
|
|
|
|
- Deployable Model: [APLUX-MODEL-FARM-LICENSE](https://aiot.aidlux.com/api/v1/files/license/model_farm_license_en.pdf) |
