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Weakly Supervised Deep Learning in Radiology
RadiologyThis review explores the transition of deep learning in radiology from laborious fully supervised methods to more scalable weakly supervised methods, emphasizing the potential and challenges for future research.
Leo Misera +3 more
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Weakly Supervised Biomedical Image Segmentation by Reiterative Learning
IEEE Journal of Biomedical and Health Informatics, 2019Recent advances in deep learning have produced encouraging results for biomedical image segmentation; however, outcomes rely heavily on comprehensive annotation. In this paper, we propose a neural network architecture and a new algorithm, known as overlapped region forecast, for the automatic segmentation of gastric cancer images.
Qiaokang Liang +7 more
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Weakly-supervised video visual knowledge learning
2019Learning video visual representation for detection has emerged as one of the fundamental problems toward general video understanding. It requires rich knowledge for spatial and/or temporal localization; however, manually collecting fully-supervised annotations is extremely expensive and not scalable.
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IEEE Transactions on Neural Networks and Learning Systems, 2022
Tao Jiang, Weiying Xie, Yunsong
exaly
Tao Jiang, Weiying Xie, Yunsong
exaly
Discrepant multiple instance learning for weakly supervised object detection
Pattern Recognition, 2022Fang Wan, Qixiang Ye
exaly
Weakly Supervised Object Detection Using Proposal- and Semantic-Level Relationships
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022Dingwen Zhang, Junwei Han
exaly
Weakly Supervised Object Localization and Detection: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021Junwei Han, Dingwen Zhang, Gong Cheng
exaly