MDMCH constructs a multiple deep hash learning framework that contains three-stream deep neural networks for images, texts, and labels.

Nov 2, 2024 · MDMCH constructs a multiple deep hash learning framework that contains three-stream deep neural networks for images, texts, and labels.

Most deep hashing methods for cross-modal retrieval use semantic labels to judge simply whether a pair of data are similar or dissimilar.

In this paper, we propose a novel tri-stage deep cross-modal hashing method – Dual. Deep Neural Networks Cross-Modal Hashing, i.e., DDCMH, which employs two ...

Multiple deep neural networks with multiple labels for cross-modal hashing retrieval ... Deng, Triplet-based deep hashing network for cross-modal retrieval, IEEE ...

4 days ago · To address these limitations, we propose a novel cross-modal retrieval approach called Multi-Label Graph Convolutional Hashing (MLGCH). MLGCH ...

Oct 20, 2024 · This paper proposes a DCGH method. Specifically, we use proxy loss as the mainstay to maintain intra-class aggregation of data, combined with pairwise loss to ...

We propose a novel multi-label contrastive semantics preserving based cross-modal hashing (MCSPH). MCSPH firstly utilizes the multiple labels of instances.

In this paper, we propose a multi-label semantics preserving based deep cross-modal hashing (MLSPH) method.

A label network is constructed to jointly guide the feature learning of different modal data and innovates discrete optimization strategies to learn hash codes ...