Deep global semantic structure-preserving hashing via corrective triplet loss for remote sensing image retrieval

Author:

Zhou Hongyan,Qin QibingORCID,Hou Jinkui,Dai Jiangyan,Huang LeiORCID,Zhang Wenfeng

Funder

Chongqing Municipal Education Commission

National Natural Science Foundation of China

Natural Science Foundation of Shandong Province

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference53 articles.

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3. Chen, Y., Zhang, S., Liu, F., Chang, Z., Ye, M., & Qi, Z. (2022). Transhash: Transformer-based hamming hashing for efficient image retrieval. In Proceedings of the 2022 international conference on multimedia retrieval (pp. 127–136).

4. Deep semantic hashing retrieval of remotec sensing images;Chen,2018

5. An image is worth 16x16 words: Transformers for image recognition at scale;Dosovitskiy,2020

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