{"title":"麻疯树反向繁殖果实模式识别系统","authors":"Z. Effendi, R. Ramli, J. Ghani, M. N. A. Rahman","doi":"10.1109/ICSIPA.2009.5478719","DOIUrl":null,"url":null,"abstract":"Jatropha curcas has been widely accepted as a favorite agricultural solution for all subtropical and tropical that can produce high quantity and quality feedstock for bio energy. Jatropha curcas oil as biodiesel feedstock has a bright prospective because it is categorized as non edible oil which the availability will not be threaten by food purposes. Traditional identification of Jatropha curcas fruits is performed by human experts. The Jatropha curcas fruit quality depends on type and size of defects as well as skin color and fruit size. This research develops a pattern recognition system to identify the Jatropha curcas fruit maturity and grade the fruit into relevant quality category. The system is divided into two stages: the first stage is a training stage that is to extract the characteristics from the pattern. The second stages is to recognize the pattern by using the characteristics derived from the first task. Back propagation diagnosis model is used to recognition the Jatropha curcas fruits. It is ascertained for the developed system is used in recognizing the maturity of Jatropha curcas fruits. This paper presents a pattern recognition system of Jatropha curcas using back propagation.","PeriodicalId":400165,"journal":{"name":"2009 IEEE International Conference on Signal and Image Processing Applications","volume":"342 ","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Pattern recognition system of Jatropha curcas fruits using back propagation\",\"authors\":\"Z. Effendi, R. Ramli, J. Ghani, M. N. A. Rahman\",\"doi\":\"10.1109/ICSIPA.2009.5478719\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Jatropha curcas has been widely accepted as a favorite agricultural solution for all subtropical and tropical that can produce high quantity and quality feedstock for bio energy. Jatropha curcas oil as biodiesel feedstock has a bright prospective because it is categorized as non edible oil which the availability will not be threaten by food purposes. Traditional identification of Jatropha curcas fruits is performed by human experts. The Jatropha curcas fruit quality depends on type and size of defects as well as skin color and fruit size. This research develops a pattern recognition system to identify the Jatropha curcas fruit maturity and grade the fruit into relevant quality category. The system is divided into two stages: the first stage is a training stage that is to extract the characteristics from the pattern. The second stages is to recognize the pattern by using the characteristics derived from the first task. Back propagation diagnosis model is used to recognition the Jatropha curcas fruits. It is ascertained for the developed system is used in recognizing the maturity of Jatropha curcas fruits. This paper presents a pattern recognition system of Jatropha curcas using back propagation.\",\"PeriodicalId\":400165,\"journal\":{\"name\":\"2009 IEEE International Conference on Signal and Image Processing Applications\",\"volume\":\"342 \",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE International Conference on Signal and Image Processing Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSIPA.2009.5478719\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE International Conference on Signal and Image Processing Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSIPA.2009.5478719","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Pattern recognition system of Jatropha curcas fruits using back propagation
Jatropha curcas has been widely accepted as a favorite agricultural solution for all subtropical and tropical that can produce high quantity and quality feedstock for bio energy. Jatropha curcas oil as biodiesel feedstock has a bright prospective because it is categorized as non edible oil which the availability will not be threaten by food purposes. Traditional identification of Jatropha curcas fruits is performed by human experts. The Jatropha curcas fruit quality depends on type and size of defects as well as skin color and fruit size. This research develops a pattern recognition system to identify the Jatropha curcas fruit maturity and grade the fruit into relevant quality category. The system is divided into two stages: the first stage is a training stage that is to extract the characteristics from the pattern. The second stages is to recognize the pattern by using the characteristics derived from the first task. Back propagation diagnosis model is used to recognition the Jatropha curcas fruits. It is ascertained for the developed system is used in recognizing the maturity of Jatropha curcas fruits. This paper presents a pattern recognition system of Jatropha curcas using back propagation.