GitHub / 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.
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PURL: pkg:github/eshansurendra/cell_anomaly_detection_using_autoencoders
Stars: 9
Forks: 0
Open issues: 0
License: mit
Language: Jupyter Notebook
Size: 2.63 MB
Dependencies parsed at:
5
Created at: over 1 year ago
Updated at: 4 months ago
Pushed at: about 1 year ago
Last synced at: 3 months ago
Topics: anomaly-detection, autoencoder, deep-learning, h5, keras, kernel-density-estimation, machine-learning, neural-network, tensorflow
- Pillow ==8.3.2
- matplotlib ==3.4.3
- numpy ==1.21.2
- scikit-learn ==0.24.2
- tensorflow ==2.6.0