Abstract: Plants are very important for life on Earth. There is a wide variety of plant species and their number increases each year. The plants identification using conventional keys is complex, takes time and it is frustrating for non-experts because of the use of specific botanical terms/techniques. This creates a difficult obstacle to overcome for novices interested in acquiring knowledge about species, which is very important to develop any environmental study, like climate change anticipation models for example. Today, there is an increasing interest in automating the species identification process. The availability and omnipresence of relevant technologies, such as digital cameras, mobile devices, pattern recognition and artificial intelligence techniques in general, have allowed the idea of automated species identification to become a reality. In this paper, we present a review of automated plant identification over all significant available studies in literature. The main result of this synthesis is that the performance of advanced deep learning models, despite the presence of several challenges, is becoming close to the most advanced human expertise.

Khaoula Labrighli, Chouaib Moujahdi, Jalal El Oualidi and Laila Rhazi, “Artificial Intelligence for Automated Plant Species Identification: A Review” International Journal of Advanced Computer Science and Applications(IJACSA), 13(10), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0131097

@article{Labrighli2022,
title = {Artificial Intelligence for Automated Plant Species Identification: A Review},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0131097},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0131097},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {10},
author = {Khaoula Labrighli and Chouaib Moujahdi and Jalal El Oualidi and Laila Rhazi}
}