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基于主动学习的相关反馈算法研究
  • ISSN号：2095-2163
  • 期刊名称：智能计算机与应用
  • 时间：2013.8.8
  • 页码：58-61
  • 分类：TP391[自动化与计算机技术—计算机应用技术;自动化与计算机技术—计算机科学与技术]
  • 作者机构：[1]哈尔滨工业大学计算机科学与技术学院,哈尔滨150001
  • 相关基金：国家自然科学基金（61171185,61271346,60932008）; 高等学校博士学科点专项科研基金（20112302110040）
  • 相关项目：大豆RNA结构与进化分析的信息处理方法研究
作者： 吴伟宁|刘扬|郭茂祖|王春宇|刘晓燕|
关键词： 基于内容图像检索, 相关反馈, 主动学习, 样本选择, Content - based Image Retrieval , Reference Feedback , Active Learning, Sampling Strategy
中文摘要：

相关反馈（reference feedback）是信息检索领域中一种常用技术,近年来,该技术被广泛应用与基于内容的图像检索（CBIR）领域中,旨在通过用户与图像检索系统间的交互过程,克服图像底层特征与高层语义之间的语义鸿沟问题。将主动学习算法结合到相关反馈技术当中,其目的是利用主动学习算法,从无标记图像集中选择最具有信息化的部分图像作为反馈图像,减少用户与系统之间的反馈次数。在COREL图像库和VOC图像库上,对基于主动学习的相关反馈技术进行实验验证,实验结果证明了,基于主动学习的相关反馈技术可以有效提高图像检索系统的性能。

英文摘要：

Reference feedback is a common technique in the field of information retrieval. Recently, it has been widely applied in the task of content - based image retrieval （CBIR） in order to overcome the gap between low features and high semantic concepts by utilizing the user - computer interaction. This paper combines the active learning into reference feedback technique. The goal is to choose the most informative images in the unlabeled pool as returned images by using the active learning, and then reduces the feedback times. On the COREL database and VOC database, the paper evaluates the proposed method. The experimental results indentify that the reference feedback based on active learning can effectively enhance the performance of CBIR system.

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期刊信息
  • 《智能计算机与应用》
  • 主管单位:中华人民共和国工业和信息化部
  • 主办单位:哈尔滨工业大学 黑龙江省信息化办公室 黑龙江省计算机用户协会 黑龙江省计算机学会
  • 主编：徐晓飞
  • 地址：哈尔滨市南岗区繁荣街155号（哈工大新技术楼916室）
  • 邮编：150001
  • 邮箱：ica@hit.edu.cn
  • 电话：0451-86413183
  • 国际标准刊号：ISSN：2095-2163
  • 国内统一刊号：ISSN：23-1573/TN
  • 邮发代号:14-144
  • 获奖情况:
  • 1988，1991，1996，2000年黑龙江省优秀科技期刊
  • 国内外数据库收录:
  • 被引量:1007