Deep Learning for Anomaly Detection in Railway Systems: A Structured Survey
cs.LG, cs.AI
Submitted: 2026-09-30
Updated: 2026-09-30
Sources
- Deep Learning for Anomaly Detection: A Survey
- An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling
- Rail-5k: a Real-World Dataset for Rail Surface Defects Detection
- A Survey on GANs for Anomaly Detection
- Meta-learning with GANs for anomaly detection, with deployment in high-speed rail inspection system
- Is AUC the best measure for practical comparison of anomaly detectors?
- A Comprehensive Survey on Hardware-Aware Neural Architecture Search
- A Survey of Model Compression and Acceleration for Deep Neural Networks
- Distilling the Knowledge in a Neural Network
- ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware
- HADAS: Hardware-Aware Dynamic Neural Architecture Search for Edge Performance Scaling
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