Data-Driven Knowledge Fusion for Deep Multi-Instance Learning

Multi-instance learning (MIL) is a widely applied technique in practical applications that involve complex data structures. MIL can be broadly categorized into two types: traditional methods and those based on deep learning. These approaches have yielded significant results, especially regarding the...

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Veröffentlicht in:	IEEE transaction on neural networks and learning systems Jg. 36; H. 5; S. 8292 - 8306
Hauptverfasser:	Zhang, Yu-Xuan, Zhou, Zhengchun, He, Xingxing, Ranjan Adhikary, Avik, Dutta, Bapi
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.05.2025
Schlagworte:	Adaptation models Analytical models Classification Classification algorithms Data models data-driven knowledge fusion (DDKF) Deep learning Feature extraction multi-instance learning (MIL) Scalability two-level attention (TLA)
ISSN:	2162-237X, 2162-2388, 2162-2388
Online-Zugang:	Volltext
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