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cs.CV2023
Towards Imbalanced Large Scale Multi-label Classification with Partially Annotated Labels
XIn Zhang, Yuqi Song, Fei Zuo +1
Multi-label classification is a widely encountered problem in daily life, where an instance can be associated with multiple classes. In theory, this is a supervised learning method…
cs.CV2023
D-Score: A White-Box Diagnosis Score for CNNs Based on Mutation Operators
Xin Zhang, Yuqi Song, Xiaofeng Wang +1
Convolutional neural networks (CNNs) have been widely applied in many safety-critical domains, such as autonomous driving and medical diagnosis. However, concerns have been raised…
cs.CV2022
PLMCL: Partial-Label Momentum Curriculum Learning for Multi-Label Image Classification
Rabab Abdelfattah, Xin Zhang, Zhenyao Wu +3
Multi-label image classification aims to predict all possible labels in an image. It is usually formulated as a partial-label learning problem, given the fact that it could be expe…