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1702752 Vol 4 · Issue 12 Download Paper

CNN Based Approach to Identify Hibiscus Plant Species

Pallavi Shetty Dr. Balasubramani R

Subject area: Science,Engineering and Technology  ·  Area of research: Deep Learning

Abstract

Plants are vital to human survival. There are numerous rare plant species that humans need in their daily lives, whether for medicinal or other purposes. It is everyone's responsibility to recognize the need for such species and protect them for future generations. As a result, identifying plant species is primarily a research platform. Because leaf images are 2D in nature, while stem images and flower images are 3D, it has been proven in the technical plant identification process that identifying a plant using its leaf images is easier than identifying a plant using other components such as stem images, flower images, and so on. As a result of considering these factors, some Hibiscus species have been detected and classified using CNN algorithm technique.

Keywords

CNN, Hibiscus Species, Deep learning algorithm, leaf data set

References

[1] M. Vilasini, P. Ramamoorthy, CNN Approaches for Classification of Indian Leaf Species Using Smartphones, Computers, Materials & Continua CMC, vol.62, no.3, pp.1445-1472, 2020

[2] Aimen Aakif, Muhammad Faisal Khan, Automatic classification of plants based on their leaves, Biosystems Engineering, vol. 139, pp. 66-75

[3] M. Jaiganesh1, M. SathyaDevi2, K. Srinivasa Chakravarthy3, Ch. Sarada, Identification of Plant Species using CNN - Classifier, JOURNAL OF CRITICAL REVIEWS ISSN - 2394-5125 VOL 7, ISSUE 3, 2020

[4] Srdjan Sladojevic,1 Marko Arsenovic,1 Andras Anderla,1 Dubravko Culibrk,2 and Darko Stefanovic, Deep Neural Networks Based and Neuroscience Volume 2016, Article ID 3289801, 11 pages.

[5] Asmaa Missoum, An update review on Hibiscus rosa sinensis phytochemistry and medicinal uses, Journal of Ayurvedic and Herbal Medicine 2018; 4(3): 135-146.

[6] Ghosh A, Dutta A. GC-MS analysis and study of potential antioxidant activity of the crude ethanolic flower extract of Hibiscus rosa sinensis L (wild variety) by hydrogen peroxide scavenging assay. International Journal of Current Trends in Science and Technology. 2017;7(11):20405–20410.

[7] Pragya Singh,1 Mahejibin Khan, Hailu Hailemariam, Nutritional and health importance of Hibiscus sabdariffa: a review and indication for research needs, Journal of Nutritional Health & Food Engineering, eISSN: 2373-4310

[8] Okereke CN, Iroka FC, Chukwuma MO. Phytochemical analysis and medicinal uses of Hibiscus sabdariffa. International Journal of Herbal Medicine. 2015;2(6):16‒19.

How to cite this paper

Pallavi Shetty, Dr. Balasubramani R "CNN Based Approach to Identify Hibiscus Plant Species" Iconic Research And Engineering Journals Volume 4 Issue 12 2021 Page 22-26
Pallavi Shetty, Dr. Balasubramani R "CNN Based Approach to Identify Hibiscus Plant Species" Iconic Research And Engineering Journals, vol. 4, no. 12, Jun. 2021
Pallavi Shetty, Dr. Balasubramani R (2021). CNN Based Approach to Identify Hibiscus Plant Species. Iconic Research And Engineering Journals, 4(12).
Pallavi Shetty, Dr. Balasubramani R "CNN Based Approach to Identify Hibiscus Plant Species" Iconic Research And Engineering Journals, vol. 4, no. 12, Jun. 2021.
@article{1702752,
      author = {Pallavi Shetty, Dr. Balasubramani R},
      title = {CNN Based Approach to Identify Hibiscus Plant Species},
      journal = {Iconic Research And Engineering Journals},
      year = {2021},
      volume = {4},
      number = {12},
      pages = {22-26},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1702752.pdf},
      abstract = {Plants are vital to human survival. There are numerous rare plant species that humans need in their daily lives, whether for medicinal or other purposes. It is everyone's responsibility to recognize the need for such species and protect them for future generations. As a result, identifying plant species is primarily a research platform. Because leaf images are 2D in nature, while stem images and flower images are 3D, it has been proven in the technical plant identification process that identifying a plant using its leaf images is easier than identifying a plant using other components such as stem images, flower images, and so on. As a result of considering these factors, some Hibiscus species have been detected and classified using CNN algorithm technique. },
      keywords = {CNN, Hibiscus Species, Deep learning algorithm, leaf data set},
      month = {June},
  }