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Design and interpretation of eQTL-GWAS colocalisation studies: lessons from a large-scale evaluation
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AGPN: Action Granularity Pyramid Network for Video Action Recognition
IEEE Transactions on Circuits and Systems for Video Technology, 2023Video action recognition is a fundamental task for video understanding. Action recognition in complex spatio-temporal contexts generally requires fusing of different multi-granularity action information.
Yatong Chen, Hongwei Ge, Yuxuan Liu
exaly +2 more sources
MGSFformer: A Multi-Granularity Spatiotemporal Fusion Transformer for air quality prediction
Information FusionAir quality spatiotemporal prediction can provide technical support for environmental governance and sustainable city development. As a classic multi-source spatiotemporal data, effective multi-source information fusion is key to achieving accurate air ...
YongJun XU, Zezhi Shao, Fei Wang
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IEEE Transactions on Pattern Analysis and Machine Intelligence
In the real world, data distributions often exhibit multiple granularities. However, the majority of existing neighbor-based machine-learning methods rely on manually setting a single-granularity for neighbor relationships. These methods typically handle
Xinbo Gao, Guoyin Wang
exaly +2 more sources
In the real world, data distributions often exhibit multiple granularities. However, the majority of existing neighbor-based machine-learning methods rely on manually setting a single-granularity for neighbor relationships. These methods typically handle
Xinbo Gao, Guoyin Wang
exaly +2 more sources
IEEE Transactions on Evolutionary Computation, 2023
Evolutionary algorithms (EAs) have shown their competitiveness in solving the problem of feature selection (FS). However, in most of the existing EA-based FS methods, one bit in the individual only represents one feature, which means with the number of ...
Fan Cheng, Jun Cui, Qi Wang, L. Zhang
semanticscholar +1 more source
Evolutionary algorithms (EAs) have shown their competitiveness in solving the problem of feature selection (FS). However, in most of the existing EA-based FS methods, one bit in the individual only represents one feature, which means with the number of ...
Fan Cheng, Jun Cui, Qi Wang, L. Zhang
semanticscholar +1 more source
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022
In the semi-supervised skeleton-based action recognition task, obtaining more discriminative information from both labeled and unlabeled data is a challenging problem.
Xiangbo Shu +3 more
semanticscholar +1 more source
In the semi-supervised skeleton-based action recognition task, obtaining more discriminative information from both labeled and unlabeled data is a challenging problem.
Xiangbo Shu +3 more
semanticscholar +1 more source
Fine-Grained Visual Classification via Progressive Multi-Granularity Training of Jigsaw Patches
European Conference on Computer Vision, 2020Fine-grained visual classification (FGVC) is much more challenging than traditional classification tasks due to the inherently subtle intra-class object variations.
Ruoyi Du +6 more
semanticscholar +1 more source
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021
Fine-grained visual classification (FGVC) is much more challenging than traditional classification tasks due to the inherently subtle intra-class object variations.
Ruoyi Du +5 more
semanticscholar +1 more source
Fine-grained visual classification (FGVC) is much more challenging than traditional classification tasks due to the inherently subtle intra-class object variations.
Ruoyi Du +5 more
semanticscholar +1 more source