Furthermore, the proposed method outperforms the recent CBIR successfully used in medical image retrieval IMTDF, and the recent cross-modal image retrieval method TC-Net (Table 3). Similarly to the representation learning of CoMIRs used in our method, TC-NET uses a contrastive loss (triplet lo...
Independent random transform TvisTvis and TothToth would be conducted on raw visible and the other modal images for two parallel self-supervised learning. 2) Overall loss function: The input is processed by the network to generate the feature map, and then the descriptors and score maps are ...
Although the fact that current methods have some effects, unsupervised cross-modal hashing methods still face several common challenges. First of all, the
Existing cross-modal hashing methods ignore the informative multimodal joint information and cannot fully exploit the semantic labels. In this paper, we propose a deep fused two-step cross-modal hashing (DFTH) framework with multiple semantic supervision. In the first step, DFTH learns unified hash...
Cross-modal Hashing has received a lot of attentions in the field of cross-modal retrieval due to its high retrieval efficiency and low storage cost. Most of the existing cross-modal Hashing methods learn Hash codes directly from multimod
et al. CMFNet: a cross-dimensional modal fusion network for accurate vessel segmentation based on OCTA data. Med Biol Eng Comput 63, 1161–1176 (2025). https://doi.org/10.1007/s11517-024-03256-z Download citation Received02 June 2024 Accepted25 November 2024 Published13 December 2024 Issue ...
The objective of the present study was to explore cross-modal associations between color and tactile sensation while using haptically rendered virtual stimuli with substance properties of roughness/smoothness, hardness/softness, heaviness/lightness, elasticity/inelasticity, and adhesiveness/nonadhesiveness. The...
Target classification and recognition for high-resolution remote sensing images: using the parallel cross-modal neural cognitive computing algorithm. IEEE Geosci Remote Sens Mag. 2020;8(3):50–62.10.1109/MGRS.2019.2949353Search in Google Scholar [6] Jagota V, Luthra M, Bhola J, Sharma A, Shabaz...
Cross-modal target retrievalShared proxy constructionThe diversity of remote sensing (RS) image modalities has expanded alongside advancements in RS technologies. A plethora of optical, multispectral, and hyperspectral RS images offer rich geographic class information. The ability to swiftly access multiple...
With the rapid advent and abundance of remote sensing data in different modalities, cross-modal retrieval tasks have gained importance in the research community. Cross-modal retrieval belongs to the research paradigm in which the query is of one modality and the retrieved output is of the other ...