Metric learning‐based whole health indicator model for industrial robots
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Intelligent Systems"
DOI: 10.1002/int.23008
Abstract: Aiming at the problems of complex structure, high components coupling, and difficultly monitoring of the whole health status with the industrial robot, a metric learning‐based whole health indicator model is proposed. First, according to the… read more here.
Keywords: metric learning; health; industrial robots; health indicator ... See more keywords
Ground Metric Learning on Graphs
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DOI: 10.1007/s10851-020-00996-z
Abstract: Optimal transport (OT) distances between probability distributions are parameterized by the ground metric they use between observations. Their relevance for real-life applications strongly hinges on whether that ground metric parameter is suitably chosen. The challenge… read more here.
Keywords: learning graphs; metric learning; ground; problem ... See more keywords
Metric learning for weather image classification
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DOI: 10.1007/s11042-017-4948-7
Abstract: Image classification is a core task in many applications of computer vision. Recognition of weather conditions based on large-volume image datasets is a challenging problem. However, there has been little research on weather-related recognition using… read more here.
Keywords: classification; metric learning; weather; image classification ... See more keywords
Independent metric learning with aligned multi-part features for video-based person re-identification
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DOI: 10.1007/s11042-018-7119-6
Abstract: Video-based person re-identification attracts wide attention because it plays a crucial role for many applications in the video surveillance. The task of video-based person re-identification is to match image sequences of the pedestrian recorded by… read more here.
Keywords: video based; person identification; part; metric learning ... See more keywords
Person re-identification based on metric learning: a survey
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DOI: 10.1007/s11042-021-10953-6
Abstract: Person re-identification is a challenging research issue in computer vision and has a broad application prospect in intelligent security. In recent years, with the emergence of large-scale person datasets and the rapid development of deep… read more here.
Keywords: distance metric; person; person identification; metric learning ... See more keywords
Performance Analysis for SVM Combining with Metric Learning
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DOI: 10.1007/s11063-017-9771-7
Abstract: This paper analyses the performance of combining Support Vector Machines (SVMs) and metric learning, in order to evaluate the effect of metric learning on improving SVM. First, we establish the sufficient condition under which the… read more here.
Keywords: performance analysis; sufficient condition; metric learning; analysis svm ... See more keywords
Making metric learning algorithms invariant to transformations using a projection metric on Grassmann manifolds
Sign Up to like & getrecommendations! Published in 2019 at "International Journal of Machine Learning and Cybernetics"
DOI: 10.1007/s13042-019-00927-4
Abstract: The requirement for suitable ways to measure the distance or similarity between data is omnipresent in machine learning, pattern recognition and data mining, but extracting such good metrics for particular problems is in general challenging.… read more here.
Keywords: projection metric; metric learning; grassmann manifolds; distance ... See more keywords
Partial label metric learning by collapsing classes
Sign Up to like & getrecommendations! Published in 2020 at "International Journal of Machine Learning and Cybernetics"
DOI: 10.1007/s13042-020-01129-z
Abstract: Partial label learning (PLL) is a weakly supervised learning framework proposed recently, in which the ground-truth label of training sample is not precisely annotated but concealed in a set of candidate labels, which makes the… read more here.
Keywords: label; metric learning; pll; accuracy ... See more keywords
Wall-climbing robot for non-destructive evaluation using impact-echo and metric learning SVM
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DOI: 10.1007/s41315-017-0028-4
Abstract: The impact-echo (IE) acoustic inspection method is a non-destructive evaluation technique, which has been widely applied to detect the defects, structural deterioration level, and thickness of plate-like concrete structures. This paper presents a novel climbing… read more here.
Keywords: metric learning; climbing robot; non destructive; robot ... See more keywords
Multi-view metric learning based on KL-divergence for similarity measurement
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DOI: 10.1016/j.neucom.2017.01.062
Abstract: In the past decades, we have witnessed a surge of interests of learning distance metrics for various image processing tasks. However, facing with features from multiple views, most metric learning methods fail to integrate compatible… read more here.
Keywords: information; multiple views; view metric; metric learning ... See more keywords
Semi-supervised metric learning in stratified spaces via intergrating local constraints and information-theoretic non-local constraints
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DOI: 10.1016/j.neucom.2018.05.089
Abstract: Abstract Considerable research efforts have been done in learning semi-supervised distance metric learning based on both manifold and cluster assumptions in the past few years. However, there is a major problem with them once they… read more here.
Keywords: learning stratified; metric learning; semi supervised; local constraints ... See more keywords