Flower Species Recognition Using Machine Learning Classifiers
DOI:
https://doi.org/10.25007/ajnu.v11n4a1636Abstract
H
Downloads
References
Bhutada, S., K. Tejaswi and S. Vineela. Flower Recognition Using Machine Learning. International Journal Of Researches In Biosciences, Agriculture And Technology, 4(2), 67-73, 2021.
Khalid, L. F., Abdulazeez, A. M., Zeebaree, D. Q., Ahmed, F. Y., & Zebari, D. A. (2021, July). Customer churn prediction in telecommunications industry based on data mining. In 2021 IEEE Symposium on Industrial Electronics & Applications (ISIEA) (pp. 1-6). IEEE.
Haji, S. H., Abdulazeez, A. M., Zeebaree, D. Q., Ahmed, F. Y., & Zebari, D. A. (2021, July). The Impact of Different Data Mining Classification Techniques in Different Datasets. In 2021 IEEE Symposium on Industrial Electronics & Applications (ISIEA) (pp. 1-6). IEEE.
P. Galdi and R. Tagliaferri, “Data mining: accuracy and error measures for classification and prediction,” Encycl. Bioinforma. Comput. Biol., pp. 431–6, 2018.
Chicho, B. T., Abdulazeez, A. M., Zeebaree, D. Q., & Zebari, D. A. (2021). Machine learning classifiers-based classification for IRIS recognition. Qubahan Academic Journal, 1(2), 106-118.
Rao, T. S., Hema, M., Priya, K. S., Krishna, K. V., & Ali, M. S. (2021). Iris Flower Classification Using Machine Learning. Network, 9(6).
Shilpi Jain, V Poojitha, “By Using Neural Network Clustering tool in MATLAB Collecting the IRIS Flower”, Proc. IEEE , vol. 109, 2020.
M. M. Mijwil and R. A. Abttan, “Utilizing the Genetic Algorithm to Pruning the C4. 5 Decision Tree Algorithm,” Asian J. Appl. Sci. ISSN 2321– 0893, vol. 9, no. 1, 2021.
Roung– Guo Huang, Sang-Hyeon Jin, Jung –Hyun Kim and Kwang- Seck Hong, “Flower Image Recognition Using Difference Image Entropy”. DOI: 10.1145/1821748.1821868
K R Rathy, Arya Vaishali, “Classification of Dataset using Efficient Neural Fuzzy Approach”, vol. 099, August 2019.
D. Decoste, E. Mjolsness. 2001. “State of the art and future prospects by using Machine Learning”, vol. 320, 2013.
Y. Lakhdoura and R. Elayachi, “Comparative Analysis of Random Forest and J48 Classifiers for ‘IRIS’ Variety Prediction,” Glob. J. Comput. Sci. Technol., 2020
L. Dhanabal and S. P. Shantharajah, “A study on NSL-KDD dataset for intrusion detection system based on classification algorithms,” Int. J. Adv. Res. Comput. Commun. Eng., vol. 4, no. 6, pp. 446–452, 2015.
Hassan, C. A. U., Khan, M. S., & Shah, M. A. (2018, September). Comparison of machine learning algorithms in data classification. In 2018 24th International Conference on Automation and Computing (ICAC) (pp. 1-6). IEEE.
Taher, K. I., Abdulazeez, A. M., & Zebari, D. A. (2021). Data Mining Classification Algorithms for Analyzing Soil Data. Asian Journal of Research in Computer Science, 17-28.
Zafeiris, D.; Rutella, S.; Ball, G.R. An Artificial Neural Network Integrated Pipeline for Biomarker Discovery Using Alzheimer’s Disease as a Case Study. Comput. Struct. Biotechnol. J. 2018, 16, 77–87.
Zebari, D. A., Abrahim, A. R., Ibrahim, D. A., Othman, G. M., & Ahmed, F. Y. (2021). Analysis of Dense Descriptors in 3D Face Recognition. In 2021 IEEE 11th International Conference on System Engineering and Technology (ICSET) (pp. 171-176). IEEE.
Abdulqadir, H. R., Abdulazeez, A. M., & Zebari, D. A. (2021). Data mining classification techniques for diabetes prediction. Qubahan Academic Journal, 1(2), 125-133.
Ibrahim, D. A., Zebari, D. A., Ahmed, F. Y., & Zeebaree, D. Q. (2021, November). Facial Expression Recognition Using Aggregated Handcrafted Descriptors based Appearance Method. In 2021 IEEE 11th International Conference on System Engineering and Technology (ICSET) (pp. 177-182). IEEE.
Y. Lakhdoura and R. Elayachi, “Comparative Analysis of Random Forest and J48 Classifiers for ‘IRIS’ Variety Prediction,” Glob. J. Comput. Sci. Technol., 2020.
D. Rana, S. P. Jena, and S. K. Pradhan, “Performance Comparison of PCA and LDA with Linear Regression and Random Forest for IRIS Flower Classification,” PalArchs J. Archaeol. EgyptEgyptology, vol. 17, no. 9, pp. 2353–2360, 2020.
K. Sarpatwar et al., “Privacy Enhanced Decision Tree Inference,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2020, pp. 34–35.
Abdulazeez, A. M., Zeebaree, D. Q., Zebari, D. A., & Hameed, T. H. (2021). Leaf Identification Based on Shape, Color, Texture and Vines Using Probabilistic Neural Network. Computación y Sistemas, 25(3), 617-631.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2022 Academic Journal of Nawroz University

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Authors retain copyright
The use of a Creative Commons License enables authors/editors to retain copyright to their work. Publications can be reused and redistributed as long as the original author is correctly attributed.
- Copyright
- The researcher(s), whether a single or joint research paper, must sell and transfer to the publisher (the Academic Journal of Nawroz University) through all the duration of the publication which starts from the date of entering this Agreement into force, the exclusive rights of the research paper/article. These rights include the translation, reuse of papers/articles, transmit or distribute, or use the material or parts(s) contained therein to be published in scientific, academic, technical, professional journals or any other periodicals including any other works derived from them, all over the world, in English and Arabic, whether in print or in electronic edition of such journals and periodicals in all types of media or formats now or that may exist in the future. Rights also include giving license (or granting permission) to a third party to use the materials and any other works derived from them and publish them in such journals and periodicals all over the world. Transfer right under this Agreement includes the right to modify such materials to be used with computer systems and software, or to reproduce or publish it in e-formats and also to incorporate them into retrieval systems.
- Reproduction, reference, transmission, distribution or any other use of the content, or any parts of the subjects included in that content in any manner permitted by this Agreement, must be accompanied by mentioning the source which is (the Academic Journal of Nawroz University) and the publisher in addition to the title of the article, the name of the author (or co-authors), journal’s name, volume or issue, publisher's copyright, and publication year.
- The Academic Journal of Nawroz University reserves all rights to publish research papers/articles issued under a “Creative Commons License (CC BY-NC-ND 4.0) which permits unrestricted use, distribution, and reproduction of the paper/article by any means, provided that the original work is correctly cited.
- Reservation of Rights
The researcher(s) preserves all intellectual property rights (except for the one transferred to the publisher under this Agreement).
- Researcher’s guarantee
The researcher(s) hereby guarantees that the content of the paper/article is original. It has been submitted only to the Academic Journal of Nawroz University and has not been previously published by any other party.
In the event that the paper/article is written jointly with other researchers, the researcher guarantees that he/she has informed the other co-authors about the terms of this agreement, as well as obtaining their signature or written permission to sign on their behalf.
The author further guarantees:
- The research paper/article does not contain any defamatory statements or illegal comments.
- The research paper/article does not violate other's rights (including but not limited to copyright, patent, and trademark rights).
This research paper/article does not contain any facts or instructions that could cause damages or harm to others, and publishing it does not lead to disclosure of any confidential information.