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Verified signature# EinsteinNet: Physics-Informed Neural Network for Image Classification EinsteinNet is a high-performance deep learning model designed for advanced image classification. It utilizes a physics-informed architecture to improve feature extraction and structural generalization in scientific and engineering datasets. ## Model Details - **Developed by:** [Ashif Ahmed Shuvo](https://huggingface.co/me-aas) - **Model type:** Convolutional Neural Network (CNN) / Physics-Informed - **Framework:** Keras / TensorFlow - **Original Source:** [Kaggle EinsteinNet (v1.0.6)](https://www.kaggle.com/models/ashifahmedshuvo/einsteinnet) - **License:** MIT ## Evaluation Results According to the performance analysis detailed in *["EinsteinNet and state-of-the-art ML models for android-based orange classification: Integration, evaluation, and deployment"](https://doi.org/10.1016/j.atech.2025.101072)* (2025), the model achieves the following benchmarks on scientific imaging tasks: | Metric | **EinsteinNet*…b49ebc2 -
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