P. G K, Virupakshaiah H K, B. P. T., A. Karegowda, Tejaswini K M, K. K.
{"title":"基于人工神经网络分类的植物叶片识别","authors":"P. G K, Virupakshaiah H K, B. P. T., A. Karegowda, Tejaswini K M, K. K.","doi":"10.1109/ICERECT56837.2022.10060430","DOIUrl":null,"url":null,"abstract":"The state-of-the-art method to find the pictographic four types of foliage (flower, fruit, medical and tree) identification is proposed. Foliage is represented by a boundary of local feature using edge detection, followed by applying convex hull algorithm. In the second phase, ANN has been applied for simulating the system using the features identified in first phase. The proposed work resulted in an average identification rate of 96.75% and 94% with training and test data.","PeriodicalId":205485,"journal":{"name":"2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Plant foliage Recognition based on Classification using Artificial Neural Network\",\"authors\":\"P. G K, Virupakshaiah H K, B. P. T., A. Karegowda, Tejaswini K M, K. K.\",\"doi\":\"10.1109/ICERECT56837.2022.10060430\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The state-of-the-art method to find the pictographic four types of foliage (flower, fruit, medical and tree) identification is proposed. Foliage is represented by a boundary of local feature using edge detection, followed by applying convex hull algorithm. In the second phase, ANN has been applied for simulating the system using the features identified in first phase. The proposed work resulted in an average identification rate of 96.75% and 94% with training and test data.\",\"PeriodicalId\":205485,\"journal\":{\"name\":\"2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)\",\"volume\":\"104 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICERECT56837.2022.10060430\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICERECT56837.2022.10060430","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Plant foliage Recognition based on Classification using Artificial Neural Network
The state-of-the-art method to find the pictographic four types of foliage (flower, fruit, medical and tree) identification is proposed. Foliage is represented by a boundary of local feature using edge detection, followed by applying convex hull algorithm. In the second phase, ANN has been applied for simulating the system using the features identified in first phase. The proposed work resulted in an average identification rate of 96.75% and 94% with training and test data.
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