9 citations · 16 across the 32 of their papers we have counts for
7 papers · 1 filter
GBRIP: Granular Ball Representation for Imbalanced Partial Label Learning
Jintao Huang, Yiu-ming Cheung, Chi-man Vong +1
Partial label learning (PLL) is a complicated weakly supervised multi-classification task compounded by class imbalance. Currently, existing methods only rely on inter-class pseudo…
Spatial-Aware Conformal Prediction for Trustworthy Hyperspectral Image Classification
Kangdao Liu, Tianhao Sun, Hao Zeng +3
Hyperspectral image (HSI) classification involves assigning unique labels to each pixel to identify various land cover categories. While deep classifiers have achieved high predict…
C-Adapter: Adapting Deep Classifiers for Efficient Conformal Prediction Sets
Kangdao Liu, Hao Zeng, Jianguo Huang +3
Conformal prediction, as an emerging uncertainty quantification technique, typically functions as post-hoc processing for the outputs of trained classifiers. To optimize the classi…
OE-BevSeg: An Object Informed and Environment Aware Multimodal Framework for Bird's-eye-view Vehicle Semantic Segmentation
Jian Sun, Yuqi Dai, Chi-Man Vong +5
Bird's-eye-view (BEV) semantic segmentation is becoming crucial in autonomous driving systems. It realizes ego-vehicle surrounding environment perception by projecting 2D multi-vie…
Weakly-supervised Semantic Segmentation via Dual-stream Contrastive Learning of Cross-image Contextual Information
Qi Lai, Chi-Man Vong
Weakly supervised semantic segmentation (WSSS) aims at learning a semantic segmentation model with only image-level tags. Despite intensive research on deep learning approaches ove…
PLOOD: Partial Label Learning with Out-of-distribution Objects
Jintao Huang, Yiu-Ming Cheung, Chi-Man Vong
Existing Partial Label Learning (PLL) methods posit that training and test data adhere to the same distribution, a premise that frequently does not hold in practical application wh…