Differential Privacy/Pseudonymization in Federated Learning for Medical Data
Implementing differential privacy and pseudonymization in TensorFlow Federated to protect patient data while maintaining model performance
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Implementing differential privacy and pseudonymization in TensorFlow Federated to protect patient data while maintaining model performance
Developed synthetic datasets using Blender/nvisii to improve LoFTR model accuracy by 12% and robustness by 10%