Oct 13, 2020 · To this end, we propose a deep Bayesian hash learning framework, called CenterHash, which can map multi-modal data into a shared Hamming space ...

Comprehensive empirical evidence shows that our method can generate effective hash codes and yield state-of-the-art performance in cross-modal retrieval on ...

Co-authors ; Deep bayesian hashing with center prior for multi-modal neuroimage retrieval. E Yang, M Liu, D Yao, B Cao, C Lian, PT Yap, D Shen. IEEE transactions ...

Feb 22, 2024 · : Deep Bayesian hashing with center prior for multi-modal neuroimage retrieval. IEEE Trans. Med. Imaging 40(2), 503–513 (2020) [DOI] [PMC ...

Multi-site MRI harmonization (MMH) helps alleviate the inter-site difference... Resource type: Article. Deep Bayesian Hashing With Center Prior for Multi-Modal ...

The proposed MTH algorithm can learn multiscale information of medical images. MTH enhances the information interaction to capture the discriminate area.

Deep Bayesian Hashing With Center Prior for Multi-Modal Neuroimage Retrieval · pdf icon · hmtl icon · 2021 (modified: 01 Nov 2022) · IEEE Trans. Medical Imaging ...

Oct 15, 2023 · Due to low computation and storage costs, hashing-based search techniques have been widely adopted for establishing image retrieval systems.

To this end, we propose a deep Bayesian hash learning framework, called CenterHash, which can map multi-modal data into a shared Hamming space and learn ...

Deep Bayesian Hashing with Center Prior for Multi-modal Neuroimage Retrieval. IEEE Transactions on Medical Imaging. 2021-02-04 | Journal article. DOI: 10.1109 ...