Enhancing weakly supervised semantic segmentation through multi-class token attention learning

Weakly supervised semantic segmentation using image-level class labels is challenging due to the limitations of Class Activation Maps (CAMs) in convolutional neural networks (CNNs), which often highlight only the most discriminative image regions. We propose the Hierarchical Multi-Class Token Attent...

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Veröffentlicht in:	The Journal of supercomputing 2025, Vol.81 (1), Article 74
Hauptverfasser:	Luo, Huilan, Zeng, Zhen
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Attention Compilers Computer Science Image enhancement Image segmentation Interpreters Labels Modules Processor Architectures Programming Languages Regularization Semantic segmentation
Online-Zugang:	Volltext
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