Multi-Label Image Classification Model Based on Multiscale Fusion and Adaptive Label Correlation

Author:

Ye Jihua,Jiang Lu,Xiao Shunjie,Zong Ye,Jiang Aiwen

Publisher

Springer Science and Business Media LLC

Reference23 articles.

1. WANG Y, HE D L, LI F, et al. Multi-label classification with label graph superimposing [J]. Proceedings of the AAAI Conference on Artificial Intelligence, 2020, 34(7): 12265–12272.

2. WANG J, YANG Y, MAO J H, et al. CNN-RNN: A unified framework for multi-label image classification [C]//2016 IEEE Conference on Computer Vision and Pattern Recognition. Las Vegas: IEEE, 2016: 2285–2294.

3. WANG Z X, CHEN T S, LI G B, et al. Multi-label image recognition by recurrently discovering attentional regions [C]//2017 IEEE International Conference on Computer Vision. Venice: IEEE, 2017: 464–472.

4. CHEN Z M, WEI X S, WANG P, et al. Multi-label image recognition with graph convolutional networks [C]//2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Long Beach: IEEE, 2019: 5172–5181.

5. YE J, HE J J, PENG X J, et al. Attention-driven dynamic graph convolutional network for multi-label image recognition [M]//European conference on computer vision. Cham: Springer, 2020: 649–665.

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