The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Deep LAC: Deep localization, alignment and classification for fine-grained recognition
Abstract
We propose a fine-grained recognition system that incorporates part localization, alignment, and classification in one deep neural network. This is a nontrivial process, as the input to the classification module should be functions that enable back-propagation in constructing the solver. Our major contribution is to propose a valve linkage function (VLF) for back-propagation chaining and form our deep localization, alignment and classification (LAC) system. The VLF can adaptively compromise the errors of classification and alignment when training the LAC model. It in turn helps update localization. The performance on fine-grained object data bears out the effectiveness of our LAC system.
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Cites
ImageNet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155
Cited by
Recent advances in convolutional neural networks
Gu, J., Wang, Z., Kuen, J., Ma, L., Shahroudy, A., Shuai, B., Liu, T., Wang, X., Wang, G., Cai, J., et al. (2018) · Pattern Recognition · doi:10.1016/j.patcog.2017.10.013 · Cited by 6,576
Learning Multi-attention Convolutional Neural Network for Fine-Grained Image Recognition
Zheng, H., Fu, J., Mei, T., & Luo, J. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.557 · Cited by 1,045
A survey on deep learning-based fine-grained object classification and semantic segmentation
Zhao, B., Feng, J., Wu, X., & Yan, S. (2017) · International Journal of Automation and Computing · doi:10.1007/s11633-017-1053-3 · Cited by 339
Metadata
- Authors
- Lin, D., Shen, X., Lu, C., & Jia, J.
- Venue
- 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
- Publisher
- IEEE
- Published
- 2015-06
- Pages
- 1666-1674
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W1955942245
- Cited by
- 345
- References
- 1
- FWCI
- 12.33
- Type
- conference paper
- Language
- en
- Open access
- closed
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