Automatic Plant Recognition: A Survey of Relevant Algorithms

• 出版年: 2022 IEEE 18th International Colloquium on Signal Processing and Applications, CSPA 2022 - Proceeding
• 第一著者: 2-s2.0-85132754076
• フォーマット: Conference paper
• 言語: English
• 出版事項: Institute of Electrical and Electronics Engineers Inc. 2022
• オンライン･アクセス: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132754076&doi=10.1109%2fCSPA55076.2022.9782022&partnerID=40&md5=4a43cee55303dbf2a3a450599bbb9b14
• DOI: 10.1109/CSPA55076.2022.9782022

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. © 2022 IEEE.