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benchmark-models

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umitkacar / synthetic-media-challenge-solutions

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DeepFake detection with Deep Tree Network (DTN) architecture - 94.5% accuracy, 45 FPS real-time processing with zero-shot learning

computer-vision deep-learning model-zoo pytorch kaggle-competition ensemble-learning transfer-learning pretrained-models data-augmentation model-deployment production-ml deepfake-detection adversarial-robustness face-forensics competition-solutions synthetic-media real-world-ai benchmark-models video-manipulation-detection face-forgery
  • Updated Nov 10, 2025
  • Python

EofK / Benchmark-16-ML-Models-Using-the-Dry-Bean-Dataset

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This project analyzed and compared the performance of 16 machine learning models on a supervised classification task using the Dry Bean dataset. This project pursued two objectives: (1) Measure how accurately each model classifies unseen bean samples, and (2) Determine each model’s runtime for its classification training and testing process.

benchmark machine-learning classification hyperparameter-tuning feature-correlation dry-bean-dataset runtime-comparisons benchmark-models
  • Updated Aug 4, 2025
  • Jupyter Notebook

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