Results 31 to 40 of about 273,362 (259)
Multi-Label Image Classification by Feature Attention Network
IEEE Access, 2019 Learning the correlation among labels is a standing-problem in the multi-label image recognition task. The label correlation is the key to solve the multi-label classification but it is too abstract to model.
Zheng Yan +3 more
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Active learning with label correlation exploration for multi‐label image classification
IET Computer Vision, 2017 Multi‐label image classification has attracted considerable attention in machine learning recently. Active learning is widely used in multi‐label learning because it can effectively reduce the human annotation workload required to construct high ...
Jian Wu +5 more
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Semi-Supervised Classification With Graph Structure Similarity and Extended Label Propagation
IEEE Access, 2019 Graph-based semi-supervised learning (GSSL) has attracted great attention over the past decade. However, there are still several open problems: (1) how to construct a graph that effectively represents the underlying structure of data and (2) how to ...
Junliang Ma, Nannan Wang, Bing Xiao
doaj +1 more source
Dynamic Online Label Distribution Feature Selection Based on Label Importance and Label Correlation
Applied SciencesExisting feature selection methods mainly target single-label learning and multi-label learning, and only a few algorithms are optimized for label distribution learning.
Weiliang Chen, Xiao Sun, Fuji Ren
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Cup‐like nuclei are a distinctive morphological feature observed in certain cases of acute lymphoblastic leukemia (ALL). We provide evidence that they characterize DUX4/ERG ALL independently of IKZF1 deletion and reveal marked mitochondrial accumulation in this ALL subset.
Chloé Arfeuille +9 more
wiley +1 more source
Correlative multi-label video annotation [PDF]
Proceedings of the 15th ACM international conference on Multimedia, 2007 Automatically annotating concepts for video is a key to semantic-level video browsing, search and navigation. The research on this topic evolved through two paradigms. The first paradigm used binary classification to detect each individual concept in a concept set.
Guo-Jun Qi +5 more
openaire +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Type 1 plasminogen deficiency (PLGD‐1) is an ultra‐rare autosomal recessive disorder caused by variants in the PLG gene and affects approximately 1.6 individuals per million. The condition is characterized by decreased plasminogen levels and impaired function, resulting in fibrin‐rich lesions on mucous membranes throughout the body.
Charles Nakar +7 more
wiley +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Pediatric radiation therapy presents unique challenges compared to adult treatments, including those of immobilization, potential need for sedation, and the critical importance of accurate, reproducible positioning. Additionally, heightened attention to imaging doses is necessary to minimize long‐term toxicity in survivors.
Parham Alaei +17 more
wiley +1 more source
Contrastive Enhanced Learning for Multi-Label Text Classification
Applied SciencesMulti-label text classification (MLTC) aims to assign appropriate labels to each document from a given set. Prior research has acknowledged the significance of label information, but its utilization remains insufficient.
Tianxiang Wu, Shuqun Yang
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Early Impact of Childhood Opportunity on Neurocognitive Outcomes in Sickle Cell Disease
Pediatric Blood &Cancer, EarlyView.ABSTRACT Introduction Neurocognitive impairment is a well‐recognized complication of sickle cell disease (SCD) that begins early in childhood and persists across development. While cerebrovascular injury contributes substantially to risk, neurocognitive deficits are also observed in children without overt or silent cerebral infarctions, suggesting ...
Julia E. LaMotte +5 more
wiley +1 more source