Concept Preserving Hashing for Semantic Image Retrieval With Concept Drift

Author:

Tian XingORCID,Ng Wing W. Y.ORCID,Wang HuiORCID

Funder

National Natural Science Foundation of China

Guangzhou Science and Technology Plan Project

EU Horizon 2020 Programme

China Scholarship Council

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Human-Computer Interaction,Information Systems,Control and Systems Engineering,Software

Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Concept drift adaptation with scarce labels: A novel approach based on diffusion and adversarial learning;Engineering Applications of Artificial Intelligence;2024-11

2. A Concept Drift Detection Algorithm for Power Data Stream;2024 6th International Conference on Energy Systems and Electrical Power (ICESEP);2024-06-21

3. Semi-supervised Concept Preserving Hashing for Image Retrieval in Non-stationary Data Environment;Proceedings of 2024 ACM ICMR Workshop on Multimodal Video Retrieval;2024-06-10

4. Self-Distillation Dual-Memory Online Hashing with Hash Centers for Streaming Data Retrieval;Proceedings of the 31st ACM International Conference on Multimedia;2023-10-26

5. Deep Incremental Hashing for Semantic Image Retrieval With Concept Drift;IEEE Transactions on Big Data;2023-08-01

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