Knowledge Commons of Institute of Automation,CAS
Intra-Class Uncertainty Loss Function for Classification | |
He, Zhu1,2; Shan, Yu1,2 | |
2021-07-05 | |
会议名称 | 2021 IEEE International Conference on Multimedia and Expo (ICME) |
会议日期 | 2021-7-5 |
会议地点 | Virtual |
出版者 | 2021 IEEE International Conference on Multimedia and Expo (ICME) |
摘要 | Most classification models can be considered as the process of matching templates. However, when intra-class uncertainty/variability is not considered, especially for datasets containing unbalanced classes, this may lead to classification errors. To address this issue, we propose a loss function with intra-class uncertainty following Gaussian distribution. Specifically, in our framework, the features extracted by deep networks of each class are characterized by independent Gaussian distribution. The parameters of distribution are learned with a likelihood regularization along with other network parameters. The means of the Gaussian play a similar role as the center anchor in existing methods, and the variance describes the uncertainty of different classes. In addition, similar to the inter-class margin in traditional loss functions, we introduce a margin to intra-class uncertainty to make each cluster more compact and reduce the imbalance of feature distribution from different categories. Based on MNIST, CIFAR, ImageNet, and Long-tailed CIFAR analyses, the proposed approach shows improved classification performance, through learning a better class representation. |
收录类别 | EI |
七大方向——子方向分类 | 图像视频处理与分析 |
国重实验室规划方向分类 | 视觉信息处理 |
是否有论文关联数据集需要存交 | 否 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/51665 |
专题 | 脑图谱与类脑智能实验室_脑网络组研究 |
作者单位 | 1.Brainnetome Center & National Laboratory of Pattern Recognition; Institute of Automation, Chinese Academy of Sciences; University of Chinese Academy of Sciences 2.School of Future Technology, University of Chinese Academy of Sciences(UCAS) |
第一作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | He, Zhu,Shan, Yu. Intra-Class Uncertainty Loss Function for Classification[C]:2021 IEEE International Conference on Multimedia and Expo (ICME),2021. |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Intra-Class_Uncertai(1510KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 |
个性服务 |
推荐该条目 |
保存到收藏夹 |
查看访问统计 |
导出为Endnote文件 |
谷歌学术 |
谷歌学术中相似的文章 |
[He, Zhu]的文章 |
[Shan, Yu]的文章 |
百度学术 |
百度学术中相似的文章 |
[He, Zhu]的文章 |
[Shan, Yu]的文章 |
必应学术 |
必应学术中相似的文章 |
[He, Zhu]的文章 |
[Shan, Yu]的文章 |
相关权益政策 |
暂无数据 |
收藏/分享 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论