Sumedh Patil, Baba Patra, Neha Goyal, Kapil O. Gupta
{"title":"利用数字化叶片识别植物物种——一个比较研究","authors":"Sumedh Patil, Baba Patra, Neha Goyal, Kapil O. Gupta","doi":"10.1109/ICOEI51242.2021.9453003","DOIUrl":null,"url":null,"abstract":"Plants play a crucial role in nature and the well-being of the population. They have a significant contribution towards ecological stability and are also sources of our needs like food, medicine, and essential commercial products. As a result of massive scale deforestation, topsoil erosion, and habitat destruction, both the number and type of plants' existing species are steadily declining. So, plantation and identification and classification of plant species are essential for preserving plant species and accelerated farm as it will help in the better understanding of plants. Nevertheless, they are difficult to exercise as plant identification needs domain knowledge and experience. However, due to advances in machine learning and deep learning, this problem is tackled correctly. Various machine Learning and Deep Learning algorithms like Support Vector Machine, Artificial Neural Network, Convolutional Neural Network, Probabilistic Neural Network have successfully experimented on plant leaf images to identify the species with near correct accuracy. This article attempts a comparative analysis of various approaches used for plant identification. Several experiments with Swedish leaves confirm the effectiveness of machine learning and CNN based classification model.","PeriodicalId":420826,"journal":{"name":"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Recognizing Plant species using Digitized leaves- A comparative study\",\"authors\":\"Sumedh Patil, Baba Patra, Neha Goyal, Kapil O. Gupta\",\"doi\":\"10.1109/ICOEI51242.2021.9453003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Plants play a crucial role in nature and the well-being of the population. They have a significant contribution towards ecological stability and are also sources of our needs like food, medicine, and essential commercial products. As a result of massive scale deforestation, topsoil erosion, and habitat destruction, both the number and type of plants' existing species are steadily declining. So, plantation and identification and classification of plant species are essential for preserving plant species and accelerated farm as it will help in the better understanding of plants. Nevertheless, they are difficult to exercise as plant identification needs domain knowledge and experience. However, due to advances in machine learning and deep learning, this problem is tackled correctly. Various machine Learning and Deep Learning algorithms like Support Vector Machine, Artificial Neural Network, Convolutional Neural Network, Probabilistic Neural Network have successfully experimented on plant leaf images to identify the species with near correct accuracy. This article attempts a comparative analysis of various approaches used for plant identification. Several experiments with Swedish leaves confirm the effectiveness of machine learning and CNN based classification model.\",\"PeriodicalId\":420826,\"journal\":{\"name\":\"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)\",\"volume\":\"95 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-06-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOEI51242.2021.9453003\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOEI51242.2021.9453003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Recognizing Plant species using Digitized leaves- A comparative study
Plants play a crucial role in nature and the well-being of the population. They have a significant contribution towards ecological stability and are also sources of our needs like food, medicine, and essential commercial products. As a result of massive scale deforestation, topsoil erosion, and habitat destruction, both the number and type of plants' existing species are steadily declining. So, plantation and identification and classification of plant species are essential for preserving plant species and accelerated farm as it will help in the better understanding of plants. Nevertheless, they are difficult to exercise as plant identification needs domain knowledge and experience. However, due to advances in machine learning and deep learning, this problem is tackled correctly. Various machine Learning and Deep Learning algorithms like Support Vector Machine, Artificial Neural Network, Convolutional Neural Network, Probabilistic Neural Network have successfully experimented on plant leaf images to identify the species with near correct accuracy. This article attempts a comparative analysis of various approaches used for plant identification. Several experiments with Swedish leaves confirm the effectiveness of machine learning and CNN based classification model.