Automated Plant Species Detection: A CNN Approach for Image Classification

Abstract

Automated plant species detection plays a crucial role in biodiversity monitoring, ecological research, and agricultural applications. In this research, I present a deep learning-based approach utilizing Convolutional Neural Networks (CNNs) for accurate and efficient plant species recognition from digital images. The proposed CNN architecture leverages its capability to automatically learn discriminative features from raw pixel data, allowing it to handle the inherent complexities and variabilities present in plant.Overall, this research presents a comprehensive investigation into utilizing deep learning techniques, specifically CNNs, for automated plant species detection. The creation of a dedicated dataset enhances the reliability and generalizability of the proposed approach, fostering the development of intelligent and scalable solutions for plant species detection in various domains Key Words: Convolutional Neural Networks, Biodiversity monitoring, Machine learning, Species identification