Zobrazeno 1 - 10
of 54
pro vyhledávání: '"Zhou, Yucan"'
Autor:
Fei, Kexiong, Zhou, Jiang, Zhou, Yucan, Gu, Xiaoyan, Fan, Haihui, Li, Bo, Wang, Weiping, Chen, Yong
Publikováno v:
In Computers & Security January 2025 148
Real-world data often follows a long-tailed distribution, which makes the performance of existing classification algorithms degrade heavily. A key issue is that samples in tail categories fail to depict their intra-class diversity. Humans can imagine
Externí odkaz:
http://arxiv.org/abs/2112.07928
Hierarchical classification is significant for complex tasks by providing multi-granular predictions and encouraging better mistakes. As the label structure decides its performance, many existing approaches attempt to construct an excellent label str
Externí odkaz:
http://arxiv.org/abs/2107.00808
Deep hashing methods have shown great retrieval accuracy and efficiency in large-scale image retrieval. How to optimize discrete hash bits is always the focus in deep hashing methods. A common strategy in these methods is to adopt an activation funct
Externí odkaz:
http://arxiv.org/abs/2102.00648
Existing video self-supervised learning methods mainly rely on trimmed videos for model training. However, trimmed datasets are manually annotated from untrimmed videos. In this sense, these methods are not really self-supervised. In this paper, we p
Externí odkaz:
http://arxiv.org/abs/2008.02711
Deep neural networks are highly effective when a large number of labeled samples are available but fail with few-shot classification tasks. Recently, meta-learning methods have received much attention, which train a meta-learner on massive additional
Externí odkaz:
http://arxiv.org/abs/2007.06240
Scene text recognition is a hot research topic in computer vision. Recently, many recognition methods based on the encoder-decoder framework have been proposed, and they can handle scene texts of perspective distortion and curve shape. Nevertheless,
Externí odkaz:
http://arxiv.org/abs/2005.10977
Publikováno v:
In Pattern Recognition April 2022 124
Publikováno v:
In Information Sciences April 2021 551:341-357
Publikováno v:
In Pattern Recognition August 2018 80:118-128