3 papers
cs.CV2024
Rethinking Multiple Instance Learning: Developing an Instance-Level Classifier via Weakly-Supervised Self-Training
Yingfan Ma, Xiaoyuan Luo, Mingzhi Yuan +2
Multiple instance learning (MIL) problem is currently solved from either bag-classification or instance-classification perspective, both of which ignore important information conta…
cs.CV2023
OpenAL: An Efficient Deep Active Learning Framework for Open-Set Pathology Image Classification
Linhao Qu, Yingfan Ma, Zhiwei Yang +2
Active learning (AL) is an effective approach to select the most informative samples to label so as to reduce the annotation cost. Existing AL methods typically work under the clos…
cs.CV2023
Rethinking Multiple Instance Learning for Whole Slide Image Classification: A Good Instance Classifier is All You Need
Linhao Qu, Yingfan Ma, Xiaoyuan Luo +2
Weakly supervised whole slide image classification is usually formulated as a multiple instance learning (MIL) problem, where each slide is treated as a bag, and the patches cut ou…