Deep consistency-preserving hash auto-encoders for neuroimage cross-modal retrieval

HIGHLIGHTS

• who: Xinyu Wang from the CollegeChongqing University have published the paper: Deep consistency-preserving hash auto-encoders for neuroimage cross-modal retrieval, in the Journal: Scientific Reports Scientific Reports of 28/Nov/2022
• what: The authors propose a Deep Consistency-Preserving Hash Auto-encoders model, called DCPHA, based on the multi-manifold property of the feature distribution for neuroimage cross-modal retrieval. The terms, notations, definitions and types involved in this work are comprehensively shown in Table 1. To solve the problem, the authors propose a multi-semantic consistency loss and a multi-manifold similarity . . .
  

   

  

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