Applying Deep Learning and Machine Learning Algorithms for The Identification of Medicinal Plant Leaves Based on Their Spectral Characteristics

Authors

  • Nidhi Tiwari Research Scholar, Department of Computer Science Engineering, Shri Ramswaroop Memorial University, Lucknow, India
  • Bineet Kumar Gupta Faculty of Computer Science and Information Systems, Shri Ramswaroop Memorial University, Lucknow, India
  • Abhijityaditya Prakash Faculty of Computer Science and Information Systems, Shri Ramswaroop Memorial University, Lucknow, India
  • Mohammad Husain Faculty of Computer Science and Information Systems, Islamic University of Madinah, Al Madinah Al Munawarah, Saudi Arabia
  • Devendra Singh Faculty of Biotechnology, Institute of Biosciences and Technology, Shri Ramswaroop Memorial University, Lucknow, India

DOI:

https://doi.org/10.17762/jaz.v44iS-5.1134

Keywords:

Medicinal Plant detection, CNN, ML, AI, DL

Abstract

The study and consideration of medicinal plants have been ongoing throughout history due to their significant role in maintaining the well-being of mammals. Although identifying medicinal plants can be a valuable skill, it is often time-consuming, tedious, and requires the expertise of a specialist. The project works on the technique of image processing, which identifies the various medicinal plants. There has been a strong emphasis on improving efficiency through the application of technology, with a focus on incorporating digital image processing and pattern recognition techniques. To ensure accurate plant identification, proposals involving the application of computer vision neural network techniques have been advanced. This approach involves neural network models such as CNN, SVM, KNN, and Navie Bay for identifying the medical plants based on their respective features. After the validation step, the project provides a classification of 92.3 precision and 90.56 F1 score.

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Published

2023-10-20

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