Attention-based semi-supervised partial label learning on web image classification

Dayuan Chen; Ying Ma

doi:10.1117/12.2646840

7 September 2022 Attention-based semi-supervised partial label learning on web image classification

Dayuan Chen, Ying Ma

Proceedings Volume 12329, Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022); 123291H (2022) https://doi.org/10.1117/12.2646840
Event: Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022), 2022, Changsha, China

Abstract

Partial label learning s a type of weakly supervised learning, which learns to predict one label as the correct answer from a given candidate label set. It is a great challenge to improve the accuracy of recognition because of the combination of the two difficult learning conditions, partial supervised learning and partial supervised learning. However, these methods all use similar matrices for tag propagation. We introduced the attention mechanism, proposed a attention-based semisupervised partial label learning (ASPLL) method to address the label contamination issue in PLL through reliable label propagation. Using attention mechanism instead of similarity matrix can significantly improve the accuracy of the algorithm. We evaluate the performance of our method on real-world web image datasets. The experimental results on the web image dataset show that in the semi supervised partial labeling web image classification, ASSPL algorithm is significantly better than the mainstream semi-supervised partial labeling learning algorithms, such as SSPL, PARM.

Citation Download Citation

Dayuan Chen and Ying Ma "Attention-based semi-supervised partial label learning on web image classification", Proc. SPIE 12329, Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022), 123291H (7 September 2022); https://doi.org/10.1117/12.2646840

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KEYWORDS

Image classification

Machine learning

Detection and tracking algorithms

Computer networks

Data modeling

Matrices

Neural networks

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