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Titlebook: Artificial Neural Networks and Machine Learning – ICANN 2022; 31st International C Elias Pimenidis,Plamen Angelov,Mehmet Aydin Conference p

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發(fā)表于 2025-3-23 11:46:14 | 只看該作者
,JointFusionNet: Parallel Learning Human Structural Local and?Global Joint Features for?3D Human Pos-of-the-art models on both intra-scenario H36M and cross-scenario 3DPW datasets and lead to appreciable improvements in poses with more similar local features. Notably, it yields an overall improvement of 3.4?mm in MPJPE (relative 6.8. improvement) over the previous best feature fusion based method?[.] on H36M dataset in 3D human pose estimation.
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發(fā)表于 2025-3-23 15:02:42 | 只看該作者
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發(fā)表于 2025-3-24 03:46:02 | 只看該作者
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發(fā)表于 2025-3-24 10:03:04 | 只看該作者
Conference proceedings 2022ed from 561 submissions. ICANN 2022 is a dual-track conference featuring tracks in brain inspired computing and machine learning and artificial neural networks, with strong cross-disciplinary interactions and applications..
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發(fā)表于 2025-3-24 11:25:53 | 只看該作者
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發(fā)表于 2025-3-24 16:09:36 | 只看該作者
0302-9743 ral Networks, ICANN 2022, held in Bristol, UK, in September 2022.. The total of 255 full papers presented in these proceedings was carefully reviewed and selected from 561 submissions. ICANN 2022 is a dual-track conference featuring tracks in brain inspired computing and machine learning and artific
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發(fā)表于 2025-3-24 20:40:42 | 只看該作者
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發(fā)表于 2025-3-25 00:07:15 | 只看該作者
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