Leaf Recognition and Tree Information Retrieval using Deep Learning

Abstract

Leaf recognition and tree information retrieval using deep learning is a novel approach to automated plant species identification and botanical data retrieval. This research leverages advanced deep-learning techniques to analyze leaf images and extract meaningful features for accurate species classification. The model employs convolutional neural networks (CNNs) to automatically learn hierarchical representations of leaf structures, enabling robust recognition across diverse plant species. Additionally, the system integrates a comprehensive tree information retrieval component, allowing users to access detailed botanical information associated with recognized species. The deep learning model is trained on a large dataset of annotated leaf images, facilitating the development of a robust and generalizable solution. The proposed system excels in accurately identifying plant species based on leaf characteristics and provides users with valuable insights into each species' ecological attributes, habitat preferences, and other relevant information. This research contributes to the field of biodiversity conservation and ecological studies by offering an efficient and automated tool for plant identification and information retrieval, paving the way for advancements in plant taxonomy and environmental monitoring.