Cargando…
Exploring Misclassification Information for Fine-Grained Image Classification
Fine-grained image classification is a hot topic that has been widely studied recently. Many fine-grained image classification methods ignore misclassification information, which is important to improve classification accuracy. To make use of misclassification information, in this paper, we propose...
Autores principales: | Wang, Da-Han, Zhou, Wei, Li, Jianmin, Wu, Yun, Zhu, Shunzhi |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8235489/ https://www.ncbi.nlm.nih.gov/pubmed/34206995 http://dx.doi.org/10.3390/s21124176 |
Ejemplares similares
-
Image local structure information learning for fine-grained visual classification
por: Lu, Jin, et al.
Publicado: (2022) -
Few-Shot Fine-Grained Image Classification via GNN
por: Zhou, Xiangyu, et al.
Publicado: (2022) -
Fine-Grained Image Classification for Crop Disease Based on Attention Mechanism
por: Yang, Guofeng, et al.
Publicado: (2020) -
Research on Classification of Fine-Grained Rock Images Based on Deep Learning
por: Liang, Yong, et al.
Publicado: (2021) -
FAD: Fine-Grained Adversarial Detection by Perturbation Intensity Classification
por: Yang, Jin-Tao, et al.
Publicado: (2023)