Long-tailed visual recognition with deep models: A methodological survey and evaluation
In the real world, large-scale datasets for visual recognition typically exhibit a long-tailed
distribution, where only a few classes contain adequate samples but the others have (much) …
distribution, where only a few classes contain adequate samples but the others have (much) …
Learning attention-guided pyramidal features for few-shot fine-grained recognition
H Tang, C Yuan, Z Li, J Tang - Pattern Recognition, 2022 - Elsevier
Few-shot fine-grained recognition (FS-FGR) aims to distinguish several highly similar
objects from different sub-categories with limited supervision. However, traditional few-shot …
objects from different sub-categories with limited supervision. However, traditional few-shot …
Boosting few-shot fine-grained recognition with background suppression and foreground alignment
Few-shot fine-grained recognition (FS-FGR) aims to recognize novel fine-grained categories
with the help of limited available samples. Undoubtedly, this task inherits the main …
with the help of limited available samples. Undoubtedly, this task inherits the main …
Traumatic brain injury (TBI) detection: past, present, and future
AT Alouani, T Elfouly - Biomedicines, 2022 - mdpi.com
Traumatic brain injury (TBI) can produce temporary biochemical imbalance due to leaks
through cell membranes or disruption of the axoplasmic flow due to the misalignment of …
through cell membranes or disruption of the axoplasmic flow due to the misalignment of …
Sim-trans: Structure information modeling transformer for fine-grained visual categorization
Fine-grained visual categorization (FGVC) aims at recognizing objects from similar
subordinate categories, which is challenging and practical for human's accurate automatic …
subordinate categories, which is challenging and practical for human's accurate automatic …
How to Handle Sketch-Abstraction in Sketch-Based Image Retrieval?
In this paper we propose a novel abstraction-aware sketch-based image retrieval framework
capable of handling sketch abstraction at varied levels. Prior works had mainly focused on …
capable of handling sketch abstraction at varied levels. Prior works had mainly focused on …
Fine-grained visual classification via internal ensemble learning transformer
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 …
recognition (FGVC) and are now considered state of the art. However, most ViT-based works …
SR-GNN: Spatial Relation-Aware Graph Neural Network for Fine-Grained Image Categorization
Over the past few years, a significant progress has been made in deep convolutional neural
networks (CNNs)-based image recognition. This is mainly due to the strong ability of such …
networks (CNNs)-based image recognition. This is mainly due to the strong ability of such …
Fine-grained recognition with learnable semantic data augmentation
Fine-grained image recognition is a longstanding computer vision challenge that focuses on
differentiating objects belonging to multiple subordinate categories within the same meta …
differentiating objects belonging to multiple subordinate categories within the same meta …
Ultra-high-resolution detector simulation with intra-event aware GAN and self-supervised relational reasoning
Simulating high-resolution detector responses is a storage-costly and computationally
intensive process that has long been challenging in particle physics. Despite the ability of …
intensive process that has long been challenging in particle physics. Despite the ability of …