多モーダル融合と自己敵対的学習に基づく軸受異常検出方法
Han Liu1, Yong Qin1, Dilong Tu1
1The State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China.
Sensors (Basel, Switzerland)
|January 28, 2026
まとめ
本研究では、多モーダルデータの融合と自己敵対的トレーニング(SAT)を使用して精度を向上させ、鉄道の騒音環境での堅牢性を向上させる、軸受異常検出のための新しいディープラーニングアプローチを紹介します。
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