| --- |
| license: mit |
| base_model: |
| - google/efficientnet-b0 |
| --- |
| |
|
|
| # EfficientNet-B0 Document Image Classifier |
|
|
| This is an image classification model based on **Google EfficientNet-B0**, fine-tuned to classify input images into one of the following 16 categories: |
|
|
| 1. **bar_chart** |
| 2. **bar_code** |
| 3. **chemistry_markush_structure** |
| 4. **chemistry_molecular_structure** |
| 5. **flow_chart** |
| 6. **icon** |
| 7. **line_chart** |
| 8. **logo** |
| 9. **map** |
| 10. **other** |
| 11. **pie_chart** |
| 12. **qr_code** |
| 13. **remote_sensing** |
| 14. **screenshot** |
| 15. **signature** |
| 16. **stamp** |
| |
| ## Citation |
| If you use this model in your work, please cite the following papers: |
| |
| ``` |
| @article{Tan2019EfficientNetRM, |
| title={EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks}, |
| author={Mingxing Tan and Quoc V. Le}, |
| journal={ArXiv}, |
| year={2019}, |
| volume={abs/1905.11946} |
| } |
| |
| @techreport{Docling, |
| author = {Deep Search Team}, |
| month = {8}, |
| title = {{Docling Technical Report}}, |
| url={https://arxiv.org/abs/2408.09869}, |
| eprint={2408.09869}, |
| doi = "10.48550/arXiv.2408.09869", |
| version = {1.0.0}, |
| year = {2024} |
| } |
| ``` |
