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Alas-V / ConvNeXt-Food-CLF-75

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ConvNeXt-CLF-75 is a food image classifier fine-tuned from ConvNeXt_tiny on a curated subset of 75 food categories from the MM-Food-100K dataset. The model is designed to serve as a semantic guide for a downstream segmentation network in a calorie‑estimation pipeline. The classifier outputs class predictions (multi-label).

open-source research computer-vision deep-learning pytorch feature-extraction image-classification transfer-learning attention-mechanism multi-label-classification machine-learning-models fine-tuning open-source-models classification-model food-recognition cbam gem-pooling food-classifier convnext food-tech
  • Updated Jul 19, 2026
  • Python
building-architectural-image-classifier

arcxteam / building-architectural-image-classifier

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Fine-Grained Image Classification of World Architecture: An EfficientNetV2 Transfer Learning Approach with Layered Regularization

deep-learning keras grad-cam image-classification transfer-learning tensorflow-serving ipynb-notebook focal-loss tensorflow-lite tflite tensorflowjs test-time-augmentation huggingface temperature-scaling discriminative-model gem-pooling efficientnetv2 cutmix-augmentation mixup-augmentation
  • Updated Jul 2, 2026
  • Jupyter Notebook

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