Neural Network Model for Detecting Leaf Diseases and Assessing Invasive Species: A Computational Approach to Ecological Preservation

MD Nahidul Sabit

doi:10.20944/preprints202410.1287.v1

Preprint Article Version 1 This version is not peer-reviewed

Version 1 : Received: 16 October 2024 / Approved: 16 October 2024 / Online: 16 October 2024 (11:46:14 CEST)

Invasive species and plant diseases are critical threats to ecosystems and agriculture worldwide. Effective early detection of these threats can significantly mitigate their impact on biodiversity and crop yields. This paper presents a neural network-based model for detecting leaf diseases and identifying invasive species using advanced image processing techniques. The model integrates edge detection, color analysis, and morphological feature extraction to assess leaf health and species type. By automating the identification process, this approach offers an efficient and scalable solution for real-time ecological monitoring, contributing to conservation and agricultural sustainability efforts.

Invasive Species; Neural Network Model; Leaf Morphology

Computer Science and Mathematics, Artificial Intelligence and Machine Learning

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Neural Network Model for Detecting Leaf Diseases and Assessing Invasive Species: A Computational Approach to Ecological Preservation

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