A Survey On Leaf Vein Morphometrics: A Deep Learning Approach to Plant Classification

Authors

  • Prof. J. N. Ekatpure  Department of Computer Engineering, SPVP’s S.B. Patil College of Engineering, Indapur, Maharashtra, India
  • Yash P. Kamble  Department of Computer Engineering, SPVP’s S.B. Patil College of Engineering, Indapur, Maharashtra, India
  • Pooja T. More  Department of Computer Engineering, SPVP’s S.B. Patil College of Engineering, Indapur, Maharashtra, India
  • Sakshi S. Patankar  Department of Computer Engineering, SPVP’s S.B. Patil College of Engineering, Indapur, Maharashtra, India

Keywords:

Leaf Morphology, Convolutional Neural Networks (CNN), Species Differentiation, Transfer Learning for Plant Classification, Deep Learning, Machine Learning Algorithms for Classification, Plant dataset

Abstract

Deep Learning techniques for plant species classification using leaf vein morphometric features. The significance of this project lies in its potential to revolutionize the field of plant species classification. By automating the identification process and reducing dependency on human expertise, the proposed approach accelerates research efforts, supports biodiversity conservation initiatives, and offers educational opportunities. As an interdisciplinary endeavor bridging Deep Learning technology and botanical research, this project contributes to scientific advancement and technological innovation.

References

  1. Willis, K.J. (ed.) 2017. State of the World’s Plants 2017. Report. Royal Botanic Gardens, Kew.
  2. Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2012). Imagenet Classification with deep convolutional neural networks. In Advances in Neural information processing systems (pp. 1097-1105).
  3. Wang, Z. (2015). The applications of deep learning on traffic Identification. BlackHat USA.
  4. Wang, D., Khosla, A., Gargeya, R., Irshad, H., & Beck, A. H. (2016). Deep learning for identifying metastatic breast cancer. arXiv preprint arXiv:1606.05718.
  5. Lee, S. H., Chan, C. S., Wilkin, P., & Remagnino, P. (2015, September). Deep-plant: Plant identification with convolutional neural networks. In Image Processing (ICIP), 2015 IEEE International Conference on 2015 Sep 27 (pp. 452-456). IEEE.
  6. Lee, S. H., Chang, Y. L., Chan, C. S., & Remagnino, P. (2016). Plant Identification system based on a convolutional neural network for the Lifeclef 2016 plant classification task. In Working notes of CLEF 2016 Conference.
  7. Lee, S. H., Chan, C. S., Mayo, S. J., & Remagnino, P. (2017). How deep Learning extracts and learns leaf features for plant classification. Pattern Recognition, 71, 1-13.
  8. Sladojevic, S., Arsenovic, M., Anderla, A., Culibrk, D., & Stefanovic, D. (2016). Deep Neural Networks Based Recognition of Plant Diseases by Leaf Image Classification. Computational Intelligence and Neuroscience, 2016.
  9. Grinblat, G. L., Uzal, L. C., Larese, M. G., & Granitto, P. M. (2016). Deep Learning for plant identification using vein morphological Patterns. Computers and Electronics in Agriculture, 127, 418-424.
  10. Larese, M. G., Namías, R., Craviotto, R. M., Arango, M. R., Gallo, C., & Granitto, P. M. (2014). Automatic classification of legumes using leaf Vein image features. Pattern Recognition, 47(1), 158-168.
  11. Reyes, A. K., Caicedo, J. C., & Camargo, J. E. (2015). Fine-tuning Deep Convolutional Networks for Plant Recognition. In CLEF (Working Notes).
  12. Gupta, S., & Mazumdar, S. G. (2013). Sobel edge detection Algorithm. International journal of computer science and management Research, 2(2), 1578-1583.

IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2023-10-30

Issue

Volume 9, Issue 10, September-October-2023

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Prof. J. N. Ekatpure, Yash P. Kamble, Pooja T. More, Sakshi S. Patankar, " A Survey On Leaf Vein Morphometrics: A Deep Learning Approach to Plant Classification" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 9, Issue 10, pp.144-152, September-October-2023.