30 citations · 50 across the 4 of their papers we have counts for
4 papers
PercentMatch: Percentile-based Dynamic Thresholding for Multi-Label Semi-Supervised Classification
Junxiang Huang, Alexander Huang, Beatriz C. Guerra +1
While much of recent study in semi-supervised learning (SSL) has achieved strong performance on single-label classification problems, an equally important yet underexplored problem…
Multi-layered Semantic Representation Network for Multi-label Image Classification
Xiwen Qu, Hao Che, Jun Huang +2
Multi-label image classification (MLIC) is a fundamental and practical task, which aims to assign multiple possible labels to an image. In recent years, many deep convolutional neu…
A Novel Global Spatial Attention Mechanism in Convolutional Neural Network for Medical Image Classification
Linchuan Xu, Jun Huang, Atsushi Nitanda +2
Spatial attention has been introduced to convolutional neural networks (CNNs) for improving both their performance and interpretability in visual tasks including image classificati…
Incorporating Multiple Cluster Centers for Multi-Label Learning
Senlin Shu, Fengmao Lv, Yan Yan +3
Multi-label learning deals with the problem that each instance is associated with multiple labels simultaneously. Most of the existing approaches aim to improve the performance of…