{"title":"Similarity-based Image Retrieval by Self-Organizing Map with Refractoriness","authors":"Kouhei Nagashima, Masao Nakada, Y. Osana","doi":"10.1109/IJCNN.2007.4371376","DOIUrl":null,"url":null,"abstract":"In this research, we proposed a similarity-based image retrieval by self-organizing map with refractoriness. In the self-organizing map with refractoriness, the plural neurons in the map layer corresponding to the input can fire sequentially because of the refractoriness. The image retrieval system using the self-organizing map with refractoriness makes use of this property in order to retrieve plural similar images. In this image retrieval system, as the image feature, not only color information but also spectrum, impression words and key words are employed. We carried out a series of computer experiments and confirmed that the effectiveness of the proposed system.","PeriodicalId":350091,"journal":{"name":"2007 International Joint Conference on Neural Networks","volume":"74 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 International Joint Conference on Neural Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IJCNN.2007.4371376","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
Abstract
In this research, we proposed a similarity-based image retrieval by self-organizing map with refractoriness. In the self-organizing map with refractoriness, the plural neurons in the map layer corresponding to the input can fire sequentially because of the refractoriness. The image retrieval system using the self-organizing map with refractoriness makes use of this property in order to retrieve plural similar images. In this image retrieval system, as the image feature, not only color information but also spectrum, impression words and key words are employed. We carried out a series of computer experiments and confirmed that the effectiveness of the proposed system.