Enhancing Plant Leaf Classification with Deep Learning: Automating Feature Extraction for Accurate Species Identification

  • Ganesh C
  • Harshavardhan G
  • Sri Keerthi N
  • et al.
N/ACitations
Citations of this article
8Readers
Mendeley users who have this article in their library.

Abstract

Plant leaf classification using deep learning provides an automated approach that surpasses traditional methods reliant on manual feature selection. Convolutional Neural Networks (CNNs) excel at learning intricate patterns from leaf images, extracting valuable features that contribute to accurate plant species identification. These models enhance classification precision by automating feature extraction, thereby improving efficiency and reliability. By leveraging deep learning, plant recognition systems can become more dependable, and their classification accuracy is significantly increased, minimizing human error and manual intervention.

Cite

CITATION STYLE

APA

Ganesh, C., Harshavardhan, G., Sri Keerthi, N. R., Yabaji, R. V., & Rajveer Yabaji, M. S. (2025). Enhancing Plant Leaf Classification with Deep Learning: Automating Feature Extraction for Accurate Species Identification. SCT Proceedings in Interdisciplinary Insights and Innovations, 3, 513. https://doi.org/10.56294/piii2025513

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free