A collaborative gated attention network for fine-grained visual classification
Q Zhu, W Kuang, Z Li - Displays, 2023 - Elsevier
Fine-grained image classification aims at subdividing large coarse-grained categories into
finer-grained subcategories. Most existing fine-grained research methods use a single …
finer-grained subcategories. Most existing fine-grained research methods use a single …
Learning enhanced features and inferring twice for fine-grained image classification
Abstract Fine-Grained Visual Categorization (FGVC) aims to distinguish between extremely
similar subordinate-level categories within the same basic-level category. Existing research …
similar subordinate-level categories within the same basic-level category. Existing research …
Aggregate attention module for fine-grained image classification
X Wang, J Shi, H Fujita, Y Zhao - Journal of Ambient Intelligence and …, 2023 - Springer
According to huge intra-class diversity and inter-class differences, fine-grained image
classification has been a difficult topic for a long time. Attention mechanism has proven to be …
classification has been a difficult topic for a long time. Attention mechanism has proven to be …
Dual attention guided multi-scale CNN for fine-grained image classification
X Liu, L Zhang, T Li, D Wang, Z Wang - Information Sciences, 2021 - Elsevier
For the classification of fine-grained images, the subtle differences among the subclasses of
the main category must be distinguished. Intuitively, the key to realizing the fine-grained …
the main category must be distinguished. Intuitively, the key to realizing the fine-grained …
Progressive co-attention network for fine-grained visual classification
Fine-grained visual classification aims to recognize images belonging to multiple sub-
categories within a same category. It is a challenging task due to the inherently subtle …
categories within a same category. It is a challenging task due to the inherently subtle …
AP-CNN: Weakly supervised attention pyramid convolutional neural network for fine-grained visual classification
Classifying the sub-categories of an object from the same super-category (eg, bird species
and cars) in fine-grained visual classification (FGVC) highly relies on discriminative feature …
and cars) in fine-grained visual classification (FGVC) highly relies on discriminative feature …
Granularity-aware distillation and structure modeling region proposal network for fine-grained image classification
X Ke, Y Cai, B Chen, H Liu, W Guo - Pattern Recognition, 2023 - Elsevier
Fine-grained visual classification (FGVC) aims to identify objects belonging to multiple sub-
categories of the same super-category. The key to solving fine-grained classification …
categories of the same super-category. The key to solving fine-grained classification …
Cross-part learning for fine-grained image classification
Recent techniques have achieved remarkable improvements depended on mining subtle
yet distinctive features for fine-grained visual classification (FGVC). While prior works directly …
yet distinctive features for fine-grained visual classification (FGVC). While prior works directly …
Multi-directional guidance network for fine-grained visual classification
S Yang, Y Jin, J Lei, S Zhang - The Visual Computer, 2024 - Springer
Fine-grained images have a high confusion among subclasses. The key to this is finding
discriminative regions that can be used for classification. The existing methods mainly use …
discriminative regions that can be used for classification. The existing methods mainly use …
Recursive multi-scale channel-spatial attention for fine-grained image classification
Fine-grained image classification is a difficult problem, and previous studies mainly
overcome this problem by locating multiple discriminative regions in different scales and …
overcome this problem by locating multiple discriminative regions in different scales and …