Label Distribution Learning for Generalizable Multisource Person Re-Identification
Sign Up to like & getrecommendations! 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
Toward Children's Empathy Ability Analysis: Joint Facial Expression Recognition and Intensity Estimation Using Label Distribution Learning
Sign Up to like & getrecommendations! 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
Sign Up to like & getrecommendations! 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
Capturing Joint Label Distribution for Multi-Label Classification Through Adversarial Learning
Sign Up to like & getrecommendations! 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
A Novel Probabilistic Label Enhancement Algorithm for Multi-label Distribution Learning
Sign Up to like & getrecommendations! 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
Sign Up to like & getrecommendations! 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
Sign Up to like & getrecommendations! 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.
Sign Up to like & getrecommendations! 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
Sequential Label Enhancement.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3214610
Abstract: Label distribution learning (LDL) is a novel machine learning paradigm for solving ambiguous tasks, where the degree to which each label describing the instance is ambiguous. However, obtaining the label distribution is high cost and… read more here.
Keywords: label distribution; label enhancement; label; sequential label ... See more keywords
Re-weighting Large Margin Label Distribution Learning for Classification.
Sign Up to like & getrecommendations! Published in 2021 at "IEEE transactions on pattern analysis and machine intelligence"
DOI: 10.1109/tpami.2021.3082623
Abstract: Label ambiguity has attracted quite some attention among the machine learning community. The latterly proposed Label Distribution Learning (LDL) can handle label ambiguity and has found wide applications in real classification problems. In the training… read more here.
Keywords: label; label distribution; classification; large margin ... See more keywords
Supervised Approach to Identify Autism Spectrum Neurological Disorder via Label Distribution Learning
Sign Up to like & getrecommendations! Published in 2022 at "Computational Intelligence and Neuroscience"
DOI: 10.1155/2022/4464603
Abstract: Autism Spectrum Disorder (ASD) is a complicated collection of neurodevelopmental illnesses characterized by a variety of developmental defects. It is a binary classification system that cannot cope with reality. Furthermore, ASD, data label noise, high… read more here.
Keywords: distribution learning; autism spectrum; distribution; label distribution ... See more keywords