|Table of Contents|

Research Advance in Long-tailed Recognition(PDF)

南京师范大学学报(工程技术版)[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2022年02期
Page:
63-72
Research Field:
计算机科学与技术
Publishing date:

Info

Title:
Research Advance in Long-tailed Recognition
Author(s):
Zhang Ming12Zhai Junhai12Xu Lei12Gao Guangyuan12
(1.School of Mathematics and Information Science,Hebei University,Baoding 071002,China)(2.Hebei Key Laboratory of Machine Learning and Computational Intelligence,Hebei University,Baoding 071002,China)
Keywords:
deep learninglong-tailed recognitioncomputer visionresearch methodneural network
PACS:
TP181
DOI:
10.3969/j.issn.1672-1292.2022.02.010
Abstract:
Long tail recognition is one of the most popular research directions in the field of deep learning. The focus of long tail recognition is to solve the computer vision recognition task of long-tail distributed data. The prominent feature of the long-tail distribution is the 2-8 distribution,that is,20% of the classes account for 80% of the sample. We call a class with a few classes that make up most of the data a header class. Classes where most classes occupy a small portion of the data are called tail classes. Firstly, various methods are introduced to solve the problem of long tail recognition. Then, they are divided into resampling,re-weighting,transfer learning,decoupling feature learning,classifier learning and other methods. Finally, our understanding of the related methods are introduced.

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