S3ACH: Semi-Supervised Semantic Adaptive Cross-Modal Hashing
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-8070-3_20
Reference32 articles.
1. Cao, M., Li, S., Li, J., Nie, L., Zhang, M.: Image-text retrieval: a survey on recent research and development. arXiv preprint arXiv:2203.14713 (2022)
2. Cheng, M., Jing, L., Ng, M.K.: Robust unsupervised cross-modal hashing for multimedia retrieval. ACM Trans. Inf. Syst. 38(3), 1–25 (2020)
3. Cheng, S., et al.: Uncertainty-aware and multigranularity consistent constrained model for semi-supervised hashing. IEEE Trans. Circuits Syst. Video Technol. 32(10), 6914–6926 (2022)
4. Chua, T.S., Tang, J., Hong, R., Li, H., Luo, Z.: Nus-wide: a real-world web image database from national university of Singapore. In: ACM International Conference on Image & Video Retrieval (2009)
5. Da, C., Xu, S., Ding, K., Meng, G., Xiang, S., Pan, C.: AMVH: asymmetric multi-valued hashing. In: 2017 IEEE, CVPR, pp. 898–906 (2017)
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