Order Learning – An Overview

Seon-Ho Lee, Nyeong-Ho Shin, Chang-Su Kim
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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.
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顺序学习-概述
顺序学习的目的是通过比较对象来学习对象之间的顺序关系。近年来,有序学习技术在各种计算机视觉任务中取得了优异的成绩。在本文中,我们提供了这些顺序学习技术的概述。首先,我们简要讨论了与顺序学习相关的常规秩估计算法。其次,我们详细回顾了顺序学习技术。第三,我们讨论了顺序学习在人脸年龄估计、历史彩色图像分类和审美质量评价三个视觉应用上的结果。
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来源期刊
APSIPA Transactions on Signal and Information Processing
APSIPA Transactions on Signal and Information Processing ENGINEERING, ELECTRICAL & ELECTRONIC-
CiteScore
8.60
自引率
6.20%
发文量
30
审稿时长
40 weeks
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