Results 21 to 30 of about 273,362 (259)
Multi-Label Image Classification with Weak Correlation Prior
CAAI Artificial Intelligence Research, 2022 Image classification is vital and basic in many data analysis domains. Since real-world images generally contain multiple diverse semantic labels, it amounts to a typical multi-label classification problem.
Xiao Ouyang +3 more
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Multi-Target Rough Sets and Their Approximation Computation with Dynamic Target Sets
Information, 2022 Multi-label learning has become a hot topic in recent years, attracting scholars’ attention, including applying the rough set model in multi-label learning.
Wenbin Zheng, Jinjin Li, Shujiao Liao
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A Structure-Induced Framework for Multi-Label Feature Selection With Highly Incomplete Labels
IEEE Access, 2020 Feature selection has shown significant promise in improving the effectiveness of multi- label learning by constructing a reduced feature space. Previous studies typically assume that label assignment is complete or partially complete; however, missing ...
Tiantian Xu, Long Zhao
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A knowledge-based approach for estimating the distribution of urban mixed land use
International Journal of Digital Earth, 2023 Estimating the proportion of land-use types in different regions is essential to promote the organization of a compact city and reduce energy consumption.
Jing Li +4 more
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Frontiers in Pharmacology, 2019 Anatomical Therapeutic Chemical (ATC) classification system proposed by the World Health Organization is a widely accepted drug classification scheme in both academic and industrial realm.
Xiangeng Wang +4 more
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Survey of Multi-label Classification Based on Supervised and Semi-supervised Learning [PDF]
Jisuanji kexue, 2022 Most of the traditional multi-label classification algorithms use supervised learning,but in real life,there are many unlabeled data.Manual tagging of all required data is costly.Semi-supervised learning algorithms can work with a large amount of ...
WU Hong-xin, HAN Meng, CHEN Zhi-qiang, ZHANG Xi-long, LI Mu-hang
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Interactive Causal Correlation Space Reshape for Multi-Label Classification.
International Journal of Interactive Multimedia and Artificial Intelligence, 2022 Most existing multi-label classification models focus on distance metrics and feature spare strategies to extract specific features of labels. Those models use the cosine similarity to construct the label correlation matrix to constraint solution space,
Chao Zhang +3 more
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Multi-Label Learning Based on Double Laplace Regularization and Causal Inference [PDF]
Jisuanji gongcheng, 2023 Label-specific features are a research hotspot in multi-label learning, which utilizes label feature extraction to solve the problem of multiple class labels in a single instance. Existing research on multi-label classification usually considers only the
Jun LUO, Qingwei GAO, Yi TAN, Dawei ZHAO, Yixiang LU, Dong SUN
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A Microblog Recommendation Method Based on Label Correlation Relationship [PDF]
Jisuanji gongcheng, 2016 A microblog recommendation method based on label correlation relationship is presented via analyzing mircoblog features and the deficiencies of existing microblog recommendation finding algorithms.Label retrieval strategy is adopted to add label for ...
MA Huifang,JIA Meihuizi,LI Xiaohong,LU Xiaoyong
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Robust Multi-Label Classification with Enhanced Global and Local Label Correlation
Mathematics, 2022 Data representation is of significant importance in minimizing multi-label ambiguity. While most researchers intensively investigate label correlation, the research on enhancing model robustness is preliminary. Low-quality data is one of the main reasons
Tianna Zhao +2 more
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