In the proposed JMH method, three types of information are used for hash learning, which come from hash codes with different lengths and the original features of the samples and label. In contrast to the existing hashing methods, JMH can learn hash codes with different lengths in one step.
In the proposed JMH method, three types of information are used for hash learning, which come from hash codes with different lengths, the original features of ...
In the proposed JMH method, three types of information are used for hash learning, which come from hash codes with different lengths, the original features of ...
In the proposed JMH method, three types of information are used for hash learning, which come from hash codes with different lengths, the original features of ...
Bibliographic details on Jointly Multiple Hash Learning.
Aug 17, 2021 · As far as we know, the proposed MOON is the first work to simultaneously learn different length hash codes without retraining in cross-media ...
The proposed MOON is the first attempt to simultaneously learn different length hash codes without retraining in cross-media retrieval.
Joint Specifics and Consistency Hash Learning for Large-Scale Cross ...
pubmed.ncbi.nlm.nih.gov › ...
Hashing offers a promising solution for large-scale cross-modal data searching by embedding the high-dimensional data into the low-dimensional similarity ...
Aug 17, 2021 · We develop a novel framework, which can simultaneously learn different length hash codes without retraining. To our knowledge, this is the first ...
Jan 10, 2022 · We propose a deep supervised hashing method, called deep multiple length hashing(DMLH), which can learn multiple length hash codes simultaneously based on a ...