These results highlight the potential of the Autoencoder–GCN pipeline as a scalable and reliable solution for AMS structure recognition under real-world constraints.

To capture temporal dynamics for trajectory prediction, LSTM networks model motion patterns across consecutive frames. Rich spatial features are extracted using DenseNet and SuperPoint, and ...

Introduction This project focuses on fault detection in turbofan engines using the NASA C-MAPSS (Commercial Modular Aero-Propulsion System Simulation) dataset, specifically the DS02 subset. The system ...

These results highlight the potential of the Autoencoder–GCN pipeline as a scalable and reliable solution for AMS structure recognition under real-world constraints.