Unsupervised Contrastive Graph Kolmogorov–Arnold Networks Enhanced Cross-Modal Retrieval Hashing
To address modality heterogeneity and accelerate large-scale retrieval, cross-modal hashing strategies generate compact binary codes that enhance computational efficiency. Existing approaches often struggle with suboptimal feature learning due to fixed activation functions and limited cross-modal in...
Saved in:
| Main Authors: | Hongyu Lin, Shaofeng Shen, Yuchen Zhang, Renwei Xia |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
|
| Series: | Mathematics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-7390/13/11/1880 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
DropKAN: Dropout Kolmogorov–Arnold Networks
by: Mohammed Ghaith Altarabichi
Published: (2025-01-01) -
Multifidelity Kolmogorov–Arnold networks
by: Amanda A Howard, et al.
Published: (2025-01-01) -
Node Classification Based on Kolmogorov-Arnold Networks
by: YUAN Lining, FENG Wengang, LIU Zhao
Published: (2025-03-01) -
Predictive modeling of flexible EHD pumps using Kolmogorov–Arnold Networks
by: Yanhong Peng, et al.
Published: (2024-12-01) -
SineKAN: Kolmogorov-Arnold Networks using sinusoidal activation functions
by: Eric Reinhardt, et al.
Published: (2025-01-01)