Brain diseases, including tumors and mental and neurological disorders, seriously threaten
the health and well-being of millions of people worldwide. Structural and functional …

Recently, self-attention mechanisms have shown impressive performance in various NLP
and CV tasks, which can help capture sequential characteristics and derive global …

Recently, vision transformers (ViTs) have been investigated in fine-grained visual
recognition (FGVC) and are now considered state of the art. However, most ViT-based works …

Fine-grained image recognition (FGIR) is a challenging task as it requires the recognition of
sub-categories with subtle differences. Recently, the swin transformer has shown impressive …

Fine-grained visual categorization (FGVC) aims at recognizing objects from similar
subordinate categories, which is challenging and practical for human's accurate automatic …

Since the introduction of the Vision Transformer (ViT), researchers have sought to make ViTs
more efficient by removing redundant information in the processed tokens. While different …

In the field of fine-grained visual recognition (FGVR), the ability to resolve minute and often
subtle differences between highly similar object categories is paramount. The advent of …

Fine-grained object recognition (FGOR) aims to learn discriminative features that can
identify the subtle distinctions between visually similar objects. However, less effort has …

The challenge of Fine-grained visual classification (FGVC) comes from the small variations
between classes and the large variations within classes. Inspired by the fact that identifying …

Learning subtle representation about object parts plays a vital role in fine-grained visual
recognition (FGVR) field. The vision transformer (ViT) achieves promising results on …