Update README.md

README.md

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 - pytorch_model_hub_mixin
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-This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
-- Library: [More Information Needed]
-- Docs: [More Information Needed]
+# ResMaskNet
+
+## Model Description
+ResMaskNet is a convolutional neural network designed for robust face recognition and mask detection. It extends the ResNet architecture with specialized layers to handle masked face detection effectively. The model can distinguish between masked and unmasked faces and performs well even with variations in lighting, angles, and occlusions.
+
+## Model Details
+- **Model Type**: Convolutional Neural Network (CNN)
+- **Architecture**: ResNet-based with custom mask detection layers
+- **Input Size**: 224x224 pixels
+- **Framework**: PyTorch
+
+## Model Sources
+- **Repository**: [GitHub Repository](https://github.com/phamquiluan/ResidualMaskingNetwork)
+- **Paper**: [Facial Expression Recognition Using Residual Masking Network](https://ieeexplore.ieee.org/document/9411919)
+
+## Citation
+If you use the ResMaskNet model in your research or application, please cite the following paper:
+
+Pham Luan, The Huynh Vu, and Tuan Anh Tran. "Facial Expression Recognition using Residual Masking Network". In: Proc. ICPR. 2020.
+
+```
+@inproceedings{pham2021facial,
+  title={Facial expression recognition using residual masking network},
+  author={Pham, Luan and Vu, The Huynh and Tran, Tuan Anh},
+  booktitle={2020 25th International Conference on Pattern Recognition (ICPR)},
+  pages={4513--4519},
+  year={2021},
+  organization={IEEE}
+}
+```
+
+## Acknowledgements
+We thank Luan Pham for generously sharing this model with a permissive license.