Results 31 to 40 of about 7,571,754 (304)
Graph-based multi-label disease prediction model learning from medical data and domain knowledge
, 2022 In recent years, the means of disease diagnosis and treatment have been improved remarkably, along with the continuous development of technology and science. Researchers have spent tremendous time and effort to build models, with an aim to assist medical
Zhang, Ji +5 more
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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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Study on Multi-label Image Classification Based on Sample Distribution Loss [PDF]
Jisuanji kexue, 2022 Different from the data distribution in general image classification scenarios,in the scenario of multi label image classification,the sample number distribution among different label categories is unbalanced,and a small number of head categories often ...
ZHU Xu-dong, XIONG Yun
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Multi-score Learning for Affect Recognition: the Case of Body Postures [PDF]
, 2011 An important challenge in building automatic affective state recognition systems is establishing the ground truth. When the groundtruth is not available, observers are often used to label training and testing sets.
Bianchi-Berthouze, N +5 more
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An Incremental Kernel Extreme Learning Machine for Multi-Label Learning With Emerging New Labels
IEEE Access, 2020 Multi-label learning with emerging new labels is a practical problem that occurs in data streams and has become an important new research issue in the area of machine learning.
Yanika Kongsorot +2 more
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Collaboration Based Multi-Label Learning
Proceedings of the AAAI Conference on Artificial Intelligence, 2019 It is well-known that exploiting label correlations is crucially important to multi-label learning. Most of the existing approaches take label correlations as prior knowledge, which may not correctly characterize the real relationships among labels.
Lei Feng 0006, Bo An 0001, Shuo He 0001
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Uncertainty Flow Facilitates Zero-Shot Multi-Label Learning in Affective Facial Analysis
Applied Sciences, 2018 Featured Application: The proposed Uncertainty Flow framework may benefit the facial analysis with its promised elevation in discriminability in multi-label affective classification tasks. Moreover, this framework also allows the efficient model training
Wenjun Bai, Changqin Quan, Zhiwei Luo
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Multi-Label Learning With Label Specific Features Using Correlation Information
IEEE Access, 2019 To deal with the problem where each instance is associated with multiple labels, a lot of multi-label learning algorithms have been developed in recent years.
Huirui Han +4 more
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Extreme Learning Machine for Multi-Label Classification
Entropy, 2016 Extreme learning machine (ELM) techniques have received considerable attention in the computational intelligence and machine learning communities because of the significantly low computational time required for training new classifiers.
Xia Sun +5 more
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Multi-instance multi-label learning
Artificial Intelligence, 2012 64 pages, 10 figures; Artificial Intelligence ...
Zhi-Hua Zhou +3 more
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