Noor Aini Mohd Roslan, Norizan Mat Diah, Z. Ibrahim, H. M. Hanum, Marina Ismail
{"title":"Automatic Plant Recognition: A Survey of Relevant Algorithms","authors":"Noor Aini Mohd Roslan, Norizan Mat Diah, Z. Ibrahim, H. M. Hanum, Marina Ismail","doi":"10.1109/CSPA55076.2022.9782022","DOIUrl":null,"url":null,"abstract":"Plants are one of the most important elements since they provide oxygen, which is necessary for human survival. Plant recognition applications have been widely developed, and these applications can help botanists tackle various real-world problems. This paper reviews machine learning and deep learning algorithms discussed for plant recognition. Different algorithms used for plant identification and recognition research between the year 2007 until the year 2020 are reviewed. The main algorithms discussed are Convolutional Neural Network (CNN), Support Vector Machine (SVM), Artificial Neural Network (ANN), and K-Nearest Neighbours (KNN). This paper also compares the performance between selected algorithms and proposes the best technique from the research outcomes.","PeriodicalId":174315,"journal":{"name":"2022 IEEE 18th International Colloquium on Signal Processing & Applications (CSPA)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 18th International Colloquium on Signal Processing & Applications (CSPA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSPA55076.2022.9782022","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Plants are one of the most important elements since they provide oxygen, which is necessary for human survival. Plant recognition applications have been widely developed, and these applications can help botanists tackle various real-world problems. This paper reviews machine learning and deep learning algorithms discussed for plant recognition. Different algorithms used for plant identification and recognition research between the year 2007 until the year 2020 are reviewed. The main algorithms discussed are Convolutional Neural Network (CNN), Support Vector Machine (SVM), Artificial Neural Network (ANN), and K-Nearest Neighbours (KNN). This paper also compares the performance between selected algorithms and proposes the best technique from the research outcomes.