Mango Leaf Disease Identification Dataset: (MLDID)

Published: 27 July 2024| Version 1 | DOI: 10.17632/jpwtpv2c4s.1
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Description

The Mango Leaf Dataset is a comprehensive collection of high-quality images of mango leaves, meticulously gathered from various regions of Bangladesh. Recognized as the national tree of Bangladesh, the mango tree, and its fruit, play a crucial role in the country's agriculture and economy, contributing billions of dollars each season and involving numerous farmers and consumers. In the context of modern agricultural advancements, the implementation of Artificial Intelligence (AI) and Machine Learning (ML) has become increasingly significant. This dataset aims to facilitate such technological integration by providing a robust image dataset focusing on mango leaf health and disease detection. Dataset Composition: - Total Images:3000 - Image Resolution: 512x512 pixels - Classes: 5 1. Healthy Leaves: 600 images 2. Gall Mid Disease: 600 images 3. Die Back Disease: 600 images 4. Bacterial Cancer Disease: 600 images 5. Anthracnose Disease: 600 images Each image in the dataset is captured with high clarity, ensuring the quality necessary for effective analysis in various technological applications, including but not limited to: - Machine Learning - Deep Learning - Image Processing This dataset is a valuable resource for researchers and practitioners aiming to develop advanced solutions for the detection and classification of mango leaf health and diseases, ultimately contributing to the improvement of agricultural practices and outcomes.

Files

Steps to reproduce

Download the zip file and extract it

Institutions

Daffodil International University

Categories

Image Processing, Disease, Machine Learning, Image Classification, Leaf Studies

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