MT-DSNet: Mix-mask teacher–student strategies and dual dynamic selection plug-in module for fine-grained image recognition
H Lu, M Han - Computer Vision and Image Understanding, 2024 - Elsevier
The fine-grained image recognition (FGIR) task aims to classify and distinguish subtle
differences between subcategories with visually similar appearances, such as bird species …
differences between subcategories with visually similar appearances, such as bird species …
Multi-granularity hypergraph-guided transformer learning framework for visual classification
J Jiang, Z Chen, F Lei, L Xu, J Huang, X Yuan - The Visual Computer, 2024 - Springer
Fine-grained single-label classification tasks aim to distinguish highly similar categories but
often overlook inter-category relationships. Hierarchical multi-granularity visual classification …
often overlook inter-category relationships. Hierarchical multi-granularity visual classification …
Research on Multi-scale CNN and Transformer-based Multi-level Multi-classification Method for Images
Q Gou, Y Ren - IEEE Access, 2024 - ieeexplore.ieee.org
With the vigorous development of digital creativity, the image data generated by it has
exploded. To effectively manage massive image data, multi-level and multi-classification …
exploded. To effectively manage massive image data, multi-level and multi-classification …
Bidirectional Logits Tree: Pursuing Granularity Reconcilement in Fine-Grained Classification
This paper addresses the challenge of Granularity Competition in fine-grained classification
tasks, which arises due to the semantic gap between multi-granularity labels. Existing …
tasks, which arises due to the semantic gap between multi-granularity labels. Existing …