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   Articles with "label distribution" as a keyword



Facial expression intensity estimation using label-distribution-learning-enhanced ordinal regression

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recommendations! Published in 2024 at "Multimedia Systems"

DOI: 10.1007/s00530-023-01219-2

Abstract: Facial expression intensity estimation has promising applications in health care and affective computing, such as monitoring patients’ pain feelings. However, labeling facial expression intensity is a specialized and time-consuming task. Ordinal regression (OR)-based methods address… read more here.

Keywords: label distribution; facial expression; intensity; expression intensity ... See more keywords

FedVC: Virtual Clients for Federated Autonomous Driving With Imbalanced Label Distribution

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recommendations! Published in 2025 at "IEEE Transactions on Consumer Electronics"

DOI: 10.1109/tce.2025.3554180

Abstract: Federated learning in autonomous driving safeguards the privacy of individual vehicles during collaborative training by avoiding the exchange of raw data. These vehicles often suffer from imbalanced label distribution, making the federated learning model developed… read more here.

Keywords: distribution; virtual clients; federated learning; imbalanced label ... See more keywords

Label Distribution Learning for Generalizable Multisource Person Re-Identification

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recommendations! Published in 2022 at "IEEE Transactions on Information Forensics and Security"

DOI: 10.1109/tifs.2022.3204219

Abstract: Person re-identification (Re-ID) is a critical technique in the video surveillance system, which has achieved significant success in the supervised setting. However, it is difficult to directly apply the supervised model to arbitrary unseen domains… read more here.

Keywords: person identification; domain; distribution; method ... See more keywords
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Toward Children's Empathy Ability Analysis: Joint Facial Expression Recognition and Intensity Estimation Using Label Distribution Learning

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recommendations! Published in 2022 at "IEEE Transactions on Industrial Informatics"

DOI: 10.1109/tii.2021.3075989

Abstract: Empathy ability is one of the most important social communication skills in early childhood development. To analyze the children's empathy ability, facial expression analysis (FEA) is an effective way due to its ability to understand… read more here.

Keywords: expression; label distribution; intensity; empathy ability ... See more keywords

Intelligent Aging Diagnosis of Conductor in Smart Grid Using Label-Distribution Deep Convolutional Neural Networks

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recommendations! Published in 2022 at "IEEE Transactions on Instrumentation and Measurement"

DOI: 10.1109/tim.2022.3141160

Abstract: Quantitatively aging diagnosis of conductor surface remains critical challenging in fault diagnosis of smart high-voltage electricity grid. Inspired by the facial age estimation in computer vision, this work proposes a label-distribution deep convolutional neural networks… read more here.

Keywords: aging diagnosis; diagnosis; loss; label distribution ... See more keywords

Class Information-Guided Personalized Federated Learning for Fault Diagnosis Under Label Distribution Skew

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recommendations! Published in 2024 at "IEEE Transactions on Instrumentation and Measurement"

DOI: 10.1109/tim.2024.3481534

Abstract: Federated learning (FL), dedicated to ensuring interclient data privacy and leveraging the private data among clients to collectively train global models, has seen widespread research in gearbox fault diagnosis in recent years. However, in gearbox… read more here.

Keywords: diagnosis; class; fault diagnosis; distribution skew ... See more keywords

Capturing Joint Label Distribution for Multi-Label Classification Through Adversarial Learning

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recommendations! Published in 2020 at "IEEE Transactions on Knowledge and Data Engineering"

DOI: 10.1109/tkde.2019.2922603

Abstract: Label correlations are important for multi-label learning. Although current multi-label learning approaches can exploit first-order, second-order, and high-order label dependencies, they fail to exploit complete label correlations, which are included in the joint label distribution… read more here.

Keywords: label; label distribution; multi label; joint label ... See more keywords
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A Novel Probabilistic Label Enhancement Algorithm for Multi-label Distribution Learning

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recommendations! Published in 2021 at "IEEE Transactions on Knowledge and Data Engineering"

DOI: 10.1109/tkde.2021.3054465

Abstract: We propose a novel probabilistic label enhancement algorithm, called PLEA, to solve challenging label distribution learning (LDL) for multi-label classification problems. We adopt the well-known maximum entropy model based label distribution learner. However, unlike the… read more here.

Keywords: novel probabilistic; label; label distribution; multi label ... See more keywords

Fast Label Enhancement for Label Distribution Learning

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recommendations! Published in 2023 at "IEEE Transactions on Knowledge and Data Engineering"

DOI: 10.1109/tkde.2021.3092406

Abstract: Label Distribution Learning (LDL) has attracted increasing research attentions due to its potential to address the label ambiguity problem in machine learning and success in many real-world applications. In LDL, it is usually expensive to… read more here.

Keywords: distribution learning; label distributions; training instances; label distribution ... See more keywords

Label Distribution Learning by Maintaining Label Ranking Relation

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recommendations! Published in 2023 at "IEEE Transactions on Knowledge and Data Engineering"

DOI: 10.1109/tkde.2021.3099294

Abstract: Label distribution learning (LDL) is a novel machine learning paradigm that can be seen as an extension of multi-label learning (MLL). Compared with MLL, the advantages of LDL are reflected in the following perspectives: (1)… read more here.

Keywords: label ranking; distribution; label distribution; ranking relation ... See more keywords

Trusted-Data-Guided Label Enhancement on Noisy Labels.

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recommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"

DOI: 10.1109/tnnls.2022.3162316

Abstract: Label distribution covers a certain number of labels, representing the degree to which each label describes the instance. Label enhancement (LE) is a procedure of recovering the label distribution from the logical labels in the… read more here.

Keywords: noise; trusted data; label distribution; label enhancement ... See more keywords