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An Ensemble Deep Learning Technique for Plant Identification

P. Siva Prasad1 , A. Senthilrajan2

Section:Technical Paper, Product Type: Journal Paper
Volume-8 , Issue-4 , Page no. 133-135, Apr-2020

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v8i4.133135

Online published on Apr 30, 2020

Copyright © P. Siva Prasad, A. Senthilrajan . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: P. Siva Prasad, A. Senthilrajan, “An Ensemble Deep Learning Technique for Plant Identification,” International Journal of Computer Sciences and Engineering, Vol.8, Issue.4, pp.133-135, 2020.

MLA Style Citation: P. Siva Prasad, A. Senthilrajan "An Ensemble Deep Learning Technique for Plant Identification." International Journal of Computer Sciences and Engineering 8.4 (2020): 133-135.

APA Style Citation: P. Siva Prasad, A. Senthilrajan, (2020). An Ensemble Deep Learning Technique for Plant Identification. International Journal of Computer Sciences and Engineering, 8(4), 133-135.

BibTex Style Citation:
@article{Prasad_2020,
author = {P. Siva Prasad, A. Senthilrajan},
title = {An Ensemble Deep Learning Technique for Plant Identification},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {4 2020},
volume = {8},
Issue = {4},
month = {4},
year = {2020},
issn = {2347-2693},
pages = {133-135},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=5090},
doi = {https://doi.org/10.26438/ijcse/v8i4.133135}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v8i4.133135}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=5090
TI - An Ensemble Deep Learning Technique for Plant Identification
T2 - International Journal of Computer Sciences and Engineering
AU - P. Siva Prasad, A. Senthilrajan
PY - 2020
DA - 2020/04/30
PB - IJCSE, Indore, INDIA
SP - 133-135
IS - 4
VL - 8
SN - 2347-2693
ER -

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Abstract

Plant identification system is helped to find unidentified plants. Plant identification is most difficult task with the existing classification algorithms. Many existing classifiers are present to identify the plant species with the help of leafs. With the various drawbacks, the system will not reach that much. In recent years, many applications belong to various domains and technologies are using the Deep Learning (DL) for rapid and better results. In this paper, the Novel Approach (NA) is introduced with the combination of CNN adopted with ensemble methods such as bagging and boosting. This paper addresses that the Convolutional Neural Network (CNN) with ensemble methods is better than Machine Learning methods to identify the plant by leaf. The ensemble methods are to improve the accuracy and sensitivity of plant identification model. The parameters such as sensitivity and accuracy are the two metrics to show the performance.

Key-Words / Index Term

CNN, Bagging, Boosting, Novel Approach

References

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[2] Anami, B. S., Suvarna, S. N., & Govardhan, A. (2010). A combined color, texture and edge features based approach for identification and classification of indian medicinal plants. International Journal of Computer Applications,6(12), 45-51.
[3] A. Aakif, M. F. Khan, "Automatic classification of plants based on their leaves", Biosyst. Eng., vol. 139, pp. 66-75, Nov. 2015.
[4] Go¨eau, H., Bonnet, P., Joly, A.: Plant identification in an open-world (lifeclef 2016). In: CLEF working notes 2016. (2016)
[5] J. Wäldchen, P. Mäder, "Plant Species Identification Using Computer Vision Techniques: A Systematic Literature Review" in Arch. Comput. Methods Eng., pp. 1-37, Jan. 2017.