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Published in 2017 at "Neurocomputing"
DOI: 10.1016/j.neucom.2016.08.146
Abstract: Abstract Dictionary learning has played an important role in the success of sparse representation. Although several dictionary learning approaches have been developed for image classification, discriminative dictionary pair learning, i.e., jointly learning a synthesis dictionary…
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Keywords:
pair learning;
dictionary pair;
discrimination;
fisher discrimination ... See more keywords
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Published in 2021 at "IEEE Access"
DOI: 10.1109/access.2021.3078232
Abstract: Polarimetric synthetic aperture radar (PolSAR) image classification has become a hot research topic in recent years. Sparse representation plays an important role in image processing. However, almost all the existing dictionary learning methods are linear…
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Keywords:
projective dictionary;
image classification;
image;
polsar image ... See more keywords
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Published in 2023 at "IEEE Transactions on Industrial Informatics"
DOI: 10.1109/tii.2022.3168300
Abstract: Industrial process data have the characteristics of less label, multimode, high dimension, containing noise, and mixing with outliers, which increase the difficulty of mode identification and anomaly detection in process monitoring using limited labeled data.…
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Keywords:
industrial process;
semi supervised;
projective dictionary;
process ... See more keywords
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Published in 2019 at "International journal of neural systems"
DOI: 10.1142/s0129065718500053
Abstract: Automatic seizure detection is extremely important in the monitoring and diagnosis of epilepsy. The paper presents a novel method based on dictionary pair learning (DPL) for seizure detection in the long-term intracranial electroencephalogram (EEG) recordings.…
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Keywords:
seizure detection;
seizure;
pair learning;
detection ... See more keywords