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https://github.com/eshansurendra/cell_anomaly_detection_using_autoencoders
This repository offers a TensorFlow-based anomaly detection system for cell images using adversarial autoencoders, capable of identifying anomalies even in contaminated datasets. Check out our code, pretrained models, and papers for more details.
https://github.com/eshansurendra/cell_anomaly_detection_using_autoencoders
anomaly-detection autoencoder deep-learning h5 keras kernel-density-estimation machine-learning neural-network tensorflow
Last synced: 2 months ago
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This repository offers a TensorFlow-based anomaly detection system for cell images using adversarial autoencoders, capable of identifying anomalies even in contaminated datasets. Check out our code, pretrained models, and papers for more details.
- Host: GitHub
- URL: https://github.com/eshansurendra/cell_anomaly_detection_using_autoencoders
- Owner: eshansurendra
- License: mit
- Created: 2024-03-14T08:24:18.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2024-06-17T12:56:22.000Z (6 months ago)
- Last Synced: 2024-06-17T14:26:15.532Z (6 months ago)
- Topics: anomaly-detection, autoencoder, deep-learning, h5, keras, kernel-density-estimation, machine-learning, neural-network, tensorflow
- Language: Jupyter Notebook
- Homepage:
- Size: 2.63 MB
- Stars: 4
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- License: LICENSE