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  • 标题:A New Automatic Method to Adjust Parameters for Object Recognition
  • 本地全文:下载
  • 作者:Issam Qaffou ; Mohamed Sadgal ; Aziz Elfazziki
  • 期刊名称:International Journal of Advanced Computer Science and Applications(IJACSA)
  • 印刷版ISSN:2158-107X
  • 电子版ISSN:2156-5570
  • 出版年度:2012
  • 卷号:3
  • 期号:9
  • DOI:10.14569/IJACSA.2012.030932
  • 出版社:Science and Information Society (SAI)
  • 摘要:To recognize an object in an image, the user must apply a combination of operators, where each operator has a set of parameters. These parameters must be “well” adjusted in order to reach good results. Usually, this adjustment is made manually by the user. In this paper we propose a new method to automate the process of parameter adjustment for an object recognition task. Our method is based on reinforcement learning, we use two types of agents: User Agent that gives the necessary information and Parameter Agent that adjusts the parameters of each operator. Due to the nature of reinforcement learning the results do not depend only on the system characteristics but also the user’s favorite choices.
  • 关键词:thesai; IJACSA; thesai.org; journal; IJACSA papers; component; Parameters adjustment; image segmentation; Q-learning; reinforcement learning.
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