Results 31 to 40 of about 9,987 (195)
Geometric Hypergraph Learning for Visual Tracking
IEEE Transactions on Cybernetics, 2017 Graph based representation is widely used in visual tracking field by finding correct correspondences between target parts in consecutive frames. However, most graph based trackers consider pairwise geometric relations between local parts. They do not make full use of the target's intrinsic structure, thereby making the representation easily disturbed ...
Dawei Du +5 more
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Hypergraph-Mlp: Learning on Hypergraphs Without Message Passing
ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)Hypergraphs are vital in modelling data with higher-order relations containing more than two entities, gaining prominence in machine learning and signal processing. Many hypergraph neural networks leverage message passing over hypergraph structures to enhance node representation learning, yielding impressive performances in tasks like hypergraph node ...
Tang, B, Chen, S, Dong, X
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Multiview Hypergraph Fusion Network for Change Detection in High-Resolution Remote Sensing Images
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingCurrently, convolutional neural networks and transformers have been the dominant paradigms for change detection (CD) thanks to their powerful local and global feature extraction capabilities. However, with the improvement of resolution, spatial, spectral,
Xue Zhao +5 more
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The Total Variation on Hypergraphs - Learning on Hypergraphs Revisited
n/a, 2013 Hypergraphs allow one to encode higher-order relationships in data and are thus a very flexible modeling tool. Current learning methods are either based on approximations of the hypergraphs via graphs or on tensor methods which are only applicable under special conditions.
M. Hein +3 more
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Edge Representation Learning with Hypergraphs
, 2021 NeurIPS ...
Jo, Jaehyeong +5 more
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Hypergraph $p$-Laplacian: A Differential Geometry View
, 2017 The graph Laplacian plays key roles in information processing of relational data, and has analogies with the Laplacian in differential geometry. In this paper, we generalize the analogy between graph Laplacian and differential geometry to the hypergraph ...
Mandic, Danilo P +2 more
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Attribute-enhanced metric learning for face retrieval
EURASIP Journal on Image and Video Processing, 2018 Metric learning is a significant factor for media retrieval. In this paper, we propose an attribute label enhanced metric learning model to assist face image retrieval.
Yuchun Fang, Qiulong Yuan
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, 2019 In this paper, we present a hypergraph neural networks (HGNN) framework for data representation learning, which can encode high-order data correlation in a hypergraph structure.
Feng, Yifan +4 more
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Consistency of Spectral Hypergraph Partitioning under Planted Partition Model
, 2016 Hypergraph partitioning lies at the heart of a number of problems in machine learning and network sciences. Many algorithms for hypergraph partitioning have been proposed that extend standard approaches for graph partitioning to the case of hypergraphs ...
Dukkipati, Ambedkar +1 more
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Vehicle Reidentification via Multifeature Hypergraph Fusion
International Journal of Digital Multimedia Broadcasting, 2021 Vehicle reidentification refers to the mission of matching vehicles across nonoverlapping cameras, which is one of the critical problems of the intelligent transportation system.
Wang Li +3 more
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