APSIPA Transactions on Signal and Information Processing > Vol 12 > Issue 1

Order Learning – An Overview

Seon-Ho Lee, School of Electrical Engineering, Korea University, Korea, Nyeong-Ho Shin, School of Electrical Engineering, Korea University, Korea, Chang-Su Kim, School of Electrical Engineering, Korea University, Korea, changsukim@korea.ac.kr
 
Suggested Citation
Seon-Ho Lee, Nyeong-Ho Shin and Chang-Su Kim (2023), "Order Learning – An Overview", APSIPA Transactions on Signal and Information Processing: Vol. 12: No. 1, e34. http://dx.doi.org/10.1561/116.00000226

Publication Date: 16 Aug 2023
© 2023 S-H. Lee, N-H. Shin and C-S. Kim
 
Subjects
 
Keywords
Order learningordinal regressionrank estimation
 

Share

Open Access

This is published under the terms of CC BY-NC.

Downloaded: 339 times

In this article:
Introduction 
Related Work 
Preliminary – Order 
Order Learning Algorithms 
Applications 
Future Work 
Conclusions 
References 

Abstract

Order learning aims to learn the ordering relationship among objects by comparing them. Recently, several order learning techniques have achieved great performances on various computer vision tasks. In this paper, we provide an overview of these order learning techniques. First, we briefly discuss conventional rank estimation algorithms related to order learning. Second, we review the order learning techniques in detail. Third, we discuss the results of order learning on three vision applications: facial age estimation, historical color image (HCI) classification, and aesthetic quality assessment.

DOI:10.1561/116.00000226