Automatic Plant Recognition: A Survey of Relevant Algorithms
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 learni...
| Published in: | 2022 IEEE 18th International Colloquium on Signal Processing and Applications, CSPA 2022 - Proceeding |
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| Main Author: | |
| Format: | Conference paper |
| Language: | English |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2022
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132754076&doi=10.1109%2fCSPA55076.2022.9782022&partnerID=40&md5=4a43cee55303dbf2a3a450599bbb9b14 |
| Summary: | 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. |
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| ISSN: | |
| DOI: | 10.1109/CSPA55076.2022.9782022 |