Ssfe-net: Self-supervised feature enhancement for ultra-fine-grained few-shot class incremental learning
Abstract Ultra-Fine-Grained Visual Categorization (ultra-FGVC) has become a popular
problem due to its great real-world potential for classifying the same or closely related …
problem due to its great real-world potential for classifying the same or closely related …
Mfvt: Multilevel feature fusion vision transformer and ramix data augmentation for fine-grained visual categorization
X Lv, H Xia, N Li, X Li, R Lan - Electronics, 2022 - mdpi.com
The introduction and application of the Vision Transformer (ViT) has promoted the
development of fine-grained visual categorization (FGVC). However, there are some …
development of fine-grained visual categorization (FGVC). However, there are some …
XMNet: XGBoost with Multitasking Network for Classification and Segmentation of Ultra-Fine-Grained Datasets
R Farag, J Demby's, M Arifuzzaman… - … Joint Conference on …, 2024 - ieeexplore.ieee.org
Classification and segmentation using ultra-fine-grained datasets can be challenging due to
the small nuances between adjacent classes. This problem can be exacerbated by the fact …
the small nuances between adjacent classes. This problem can be exacerbated by the fact …
Diving into Continual Ultra-fine-grained Visual Categorization
Recent advance in ultra-fine-grained visual categorization (ultra-FGVC) has significantly
boosted the capability of deep neural networks for ultra-FGVC tasks. However, building …
boosted the capability of deep neural networks for ultra-FGVC tasks. However, building …
What EXACTLY are We Looking at?: Investigating for Discriminance in Ultra-Fine-Grained Visual Categorization Tasks
Comparing discriminative features at different levels of granularity is an inherent part of the
human object recognition process and AI-based models mimic such behaviour with …
human object recognition process and AI-based models mimic such behaviour with …