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Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3146339
Abstract: With the development of deep convolution neural networks (CNNs), contour detection has made great progress. Some contour detectors based on CNNs have better performance than human beings on standard benchmarks. However, it is easier for…
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Keywords:
bidirectional multiscale;
refinement network;
refinement;
multiscale refinement ... See more keywords
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Published in 2022 at "IEEE MultiMedia"
DOI: 10.1109/mmul.2022.3142154
Abstract: Multiview multilabel (MVML) learning deals with objects with diverse feature vectors and rich semantics. Existing methods are built on a shared latent space among multiple views. However, they do not well capture semantic consistency and…
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Keywords:
multiview multilabel;
personalized relation;
refinement network;
relation refinement ... See more keywords
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Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3201883
Abstract: Zero-shot learning (ZSL) aims to recognize novel categories by merely utilizing disjoint seen samples. It is a challenging task as the knowledge of unseen objects is forbidden in the training stage, which easily leads to…
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Keywords:
visual centers;
network;
refinement network;
differential refinement ... See more keywords