G. Perelmuter, Paula Pereira, M. Vellasco, M. Pacheco, E. Carrera
{"title":"利用人工智能技术对二维图像进行分类","authors":"G. Perelmuter, Paula Pereira, M. Vellasco, M. Pacheco, E. Carrera","doi":"10.1109/CYBVIS.1996.629437","DOIUrl":null,"url":null,"abstract":"This article presents the structure of an \"intelligent classifier\" composed of three modules: 1) the preprocessor, responsible for the transformation of the raw image; 2) the characteristics extractor, implemented by a genetic algorithm, which is responsible for the selection of the most relevant coefficients; and 3) the classifier, implemented by a neural network. Generic algorithms have been used as a search technique for large sets of data and neural networks, due to their ability to extract information from complex sets of data, have been largely applied in computer vision for pattern classification. The complete image classification system is invariant to translation rotation and sizing of the analysed object.","PeriodicalId":103287,"journal":{"name":"Proceedings II Workshop on Cybernetic Vision","volume":"98 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Classification of bidimensional images using artificial intelligence techniques\",\"authors\":\"G. Perelmuter, Paula Pereira, M. Vellasco, M. Pacheco, E. Carrera\",\"doi\":\"10.1109/CYBVIS.1996.629437\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article presents the structure of an \\\"intelligent classifier\\\" composed of three modules: 1) the preprocessor, responsible for the transformation of the raw image; 2) the characteristics extractor, implemented by a genetic algorithm, which is responsible for the selection of the most relevant coefficients; and 3) the classifier, implemented by a neural network. Generic algorithms have been used as a search technique for large sets of data and neural networks, due to their ability to extract information from complex sets of data, have been largely applied in computer vision for pattern classification. The complete image classification system is invariant to translation rotation and sizing of the analysed object.\",\"PeriodicalId\":103287,\"journal\":{\"name\":\"Proceedings II Workshop on Cybernetic Vision\",\"volume\":\"98 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-12-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings II Workshop on Cybernetic Vision\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CYBVIS.1996.629437\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings II Workshop on Cybernetic Vision","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CYBVIS.1996.629437","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Classification of bidimensional images using artificial intelligence techniques
This article presents the structure of an "intelligent classifier" composed of three modules: 1) the preprocessor, responsible for the transformation of the raw image; 2) the characteristics extractor, implemented by a genetic algorithm, which is responsible for the selection of the most relevant coefficients; and 3) the classifier, implemented by a neural network. Generic algorithms have been used as a search technique for large sets of data and neural networks, due to their ability to extract information from complex sets of data, have been largely applied in computer vision for pattern classification. The complete image classification system is invariant to translation rotation and sizing of the analysed object.