Academic Venue Recommendations Based on Similarity Learning of an Extended Nearby Citation Network
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DOI: 10.1109/access.2019.2906106
Abstract: The rapidly increasing number of potential academic venues for research publication and commentary has made sourcing the venue that would best contribute to promoting effective scientific cooperation more challenging. In this paper, we propose a… read more here.
Keywords: network; venue; citation network; similarity learning ... See more keywords
Improve Deep Unsupervised Hashing via Structural and Intrinsic Similarity Learning
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DOI: 10.1109/lsp.2022.3148674
Abstract: Hashing has attracted increasing attention in image retrieval recently due to its storage and computational efficiency. Although several deep unsupervised hashing methods have been proposed lately, their effectiveness is far from satisfactory in practice owing… read more here.
Keywords: unsupervised hashing; similarity; deep unsupervised; intrinsic similarity ... See more keywords
Hierarchical Deep Multitask Learning With the Attention Mechanism for Similarity Learning
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DOI: 10.1109/tcds.2021.3137316
Abstract: Similarity learning is often adopted as an auxiliary task of deep multitask learning methods to learn discriminant features. Most existing approaches only use the single-layer features extracted by the last fully connected layer, which ignores… read more here.
Keywords: similarity; multitask learning; deep multitask; similarity learning ... See more keywords
Geometry-Aware Similarity Learning on SPD Manifolds for Visual Recognition
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DOI: 10.1109/tcsvt.2017.2729660
Abstract: Symmetric positive definite (SPD) matrices have been employed for data representation in many visual recognition tasks. The success is mainly attributed to learning discriminative SPD matrices encoding the Riemannian geometry of the underlying SPD manifolds.… read more here.
Keywords: similarity learning; spd manifolds; geometry; geometry aware ... See more keywords
Deep Hybrid Similarity Learning for Person Re-Identification
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DOI: 10.1109/tcsvt.2017.2734740
Abstract: Person re-identification (Re-ID) aims to match person images captured from two non-overlapping cameras. In this paper, a deep hybrid similarity learning (DHSL) method for person Re-ID based on a convolution neural network (CNN) is proposed.… read more here.
Keywords: person identification; similarity; similarity learning; person ... See more keywords