您当前所在位置: 首页 > 学者

胡清华

  • 26浏览

  • 0点赞

  • 0收藏

  • 0分享

  • 0下载

  • 0评论

  • 引用

期刊论文

Deep Fuzzy Tree for Large-Scale Hierarchical Visual Classification

暂无

IEEE Transactions on Fuzzy Systems,2019,28(7): 1395 - 14 | 2019年08月21日 | 10.1109/TFUZZ.2019.2936801

URL:https://ieeexplore.ieee.org/document/8809246

摘要/描述

Deep learning models often use a flat softmax layer to classify samples after feature extraction in visual classification tasks. However, it is hard to make a single decision of finding the true label from massive classes. In this scenario, hierarchical classification is proved to be an effective solution and can be utilized to replace the softmax layer. A key issue of hierarchical classification is to construct a good label structure, which is very significant for classification performance. Several works have been proposed to address the issue, but they have some limitations and are almost designed heuristically. In this article, inspired by fuzzy rough set theory, we propose a deep fuzzy tree model which learns a better tree structure and classifiers for hierarchical classification with theory guarantee. Experimental results show the effectiveness and efficiency of the proposed model in various visual classification datasets.

关键词:

【免责声明】以下全部内容由[胡清华]上传于[2020年11月11日 11时05分49秒],版权归原创者所有。本文仅代表作者本人观点,与本网站无关。本网站对文中陈述、观点判断保持中立,不对所包含内容的准确性、可靠性或完整性提供任何明示或暗示的保证。请读者仅作参考,并请自行承担全部责任。

我要评论

全部评论 0

本学者其他成果

    同领域成果