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Multi-View Multi-Label Learning With View-Label-Specific Features
IEEE Access, 2019 In multi-view multi-label learning, each object is represented by multiple data views, and belongs to multiple class labels simultaneously. Generally, all the data views have a contribution to the multi-label learning task, but their contributions are ...
Jun Huang +5 more
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Journal of King Saud University: Computer and Information SciencesDespite significant advancements in multi-view multi-label learning driven by its broad applicability, real-world scenarios frequently suffer from dual incompleteness in both view and label spaces due to data acquisition uncertainties. The incompleteness
Shenrun Ding +4 more
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MS-ANet: deep learning for automated multi-label thoracic disease detection and classification [PDF]
PeerJ Computer Science, 2021 The chest X-ray is one of the most common radiological examination types for the diagnosis of chest diseases. Nowadays, the automatic classification technology of radiological images has been widely used in clinical diagnosis and treatment plans. However,
Jing Xu, Hui Li, Xiu Li
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Recognition of RNA-Binding Protein by Fusion of Multi-view and Multi-label Learning
Jisuanji kexue yu tansuo, 2021 RNA-binding protein (RBP) is a total name of a class of proteins that bind to RNA (ribonucleic acid) along with the process of RNA??s regulation metabolic.
YANG Haitao, DENG Zhaohong, WANG Shitong
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Robust Cross-View Embedding With Discriminant Structure for Multi-Label Classification
IEEE Access, 2021 Label embedding is an important family of multi-label classification algorithms which can jointly extract the information of all labels for better performance.
Kaixiang Wang
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Remote Sensing, 2020 In outdoor Light Detection and Ranging (lidar)point cloud classification, finding the discriminative features for point cloud perception and scene understanding represents one of the great challenges.
Guofeng Tong +5 more
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Use of Domain Labels during Pre-Training for Domain-Independent WiFi-CSI Gesture Recognition
Sensors, 2023 To minimize dependency on the availability of data labels, some WiFi-CSI based-gesture recognition solutions utilize an unsupervised representation learning phase prior to fine-tuning downstream task classifiers.
Bram van Berlo +2 more
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Tencent AVS: A Holistic Ads Video Dataset for Multi-Modal Scene Segmentation
IEEE Access, 2022 Temporal video segmentation and classification have been advanced greatly by public benchmarks in recent years. However, such research still mainly focuses on human actions, failing to describe videos in a holistic view.
Jie Jiang +5 more
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Incomplete Multi-view Classification via Discriminative and Sparse Representation
Jisuanji kexue yu tansuo, 2021 Generally, the traditional multi-view learning methods assume that all samples are completed in all views. However, this assumption often fails in real applications because of limited access to data, equipment malfunc-tion, as well as occlusion and so on.
XIN Like, YANG Wanqi, YANG Ming
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Multi-Label Data Fusion to Support Agricultural Vulnerability Assessments
IEEE Access, 2021 Identifying crop species and varieties adaptable to climate change impacts is one of the main aspects of climate vulnerability assessments. This estimation involves processing, integrating, and analyzing many information sources to provide accurate and ...
Ivan Dario Lopez +2 more
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