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Research Article | Open Access |

Artificial Intelligence for Automated Plant Species Identification: A Review

Author 1: Khaoula Labrighli Author 2: Chouaib Moujahdi Author 3: Jalal El Oualidi Author 4: Laila Rhazi
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 13, No. 10 · Published 2022

DOI: https://doi.org/10.14569/IJACSA.2022.0131097

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.

Keywords

How to Cite this Article

Labrighli, K., Moujahdi, C., Oualidi, J. E., & Rhazi, L. (2022). Artificial Intelligence for Automated Plant Species Identification: A Review. International Journal of Advanced Computer Science and Applications, 13(10). https://doi.org/10.14569/IJACSA.2022.0131097

Labrighli, Khaoula, et al.. "Artificial Intelligence for Automated Plant Species Identification: A Review." International Journal of Advanced Computer Science and Applications, vol. 13, no. 10, 2022, https://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},
  volume    = {13},
  number    = {10},
  year      = {2022},
  publisher = {The Science and Information Organization},
  author    = {Khaoula Labrighli and Chouaib Moujahdi and Jalal El Oualidi and Laila Rhazi},
  doi       = {10.14569/IJACSA.2022.0131097},
  url       = {https://doi.org/10.14569/IJACSA.2022.0131097}
}

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