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Xuanyuan Xie and Jieyu Zhao
The diffusion model has made progress in the field of image synthesis, especially in the area of conditional image synthesis. However, this improvement is highly dependent on large annotated datasets. To tackle this challenge, we present the Guided Diffu...
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Jie Wang, Jie Yang, Jiafan He and Dongliang Peng
Semi-supervised learning has been proven to be effective in utilizing unlabeled samples to mitigate the problem of limited labeled data. Traditional semi-supervised learning methods generate pseudo-labels for unlabeled samples and train the classifier us...
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Chunling Wang, Tianyi Hang, Changke Zhu and Qi Zhang
The Czech Republic is one of the countries along the Belt and Road Initiative, and classifying land cover in the Czech Republic helps to understand the distribution of its forest resources, laying the foundation for forestry cooperation between China and...
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Zongshun Wang, Ce Li, Jialin Ma, Zhiqiang Feng and Limei Xiao
In this study, we introduce a novel framework for the semantic segmentation of point clouds in autonomous driving scenarios, termed PVI-Net. This framework uniquely integrates three different data perspectives?point clouds, voxels, and distance maps?exec...
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Qishun Mei and Xuhui Li
To address the limitations of existing methods of short-text entity disambiguation, specifically in terms of their insufficient feature extraction and reliance on massive training samples, we propose an entity disambiguation model called COLBERT, which f...
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