FabianCormier/Cross-Domain-transfer-learning-from-Human-Motion-to-Robot-Fault-Detection

The code trains an LSTM-based residual model on human motion data and applies transfer learning to detect robotic joint faults. It preprocesses data, maps robot features to human-like patterns, and fine-tunes a model while freezing early layers. The optimized model is evaluated with class weighting, callbacks, and feature importance analysis.