Mango Leaf Disease Detection Dataset Using Deep Learning

Published: 3 March 2025| Version 2 | DOI: 10.17632/sd8hzpg69b.2
Contributor:
Robiul Awoal

Description

Dataset Overview: This dataset contains images of mango leaves collected from various mango orchards to aid in deep learning-based disease detection. The images have been preprocessed and categorized into healthy and diseased classes. The dataset aims to support research on plant disease detection, particularly for mango orchards. Preprocessing Techniques: ✅ Resizing to maintain uniform image dimensions ✅ Data Augmentation (Rotation, Flipping, Shifting) to increase dataset variability ✅ Gamma Correction for brightness adjustment and enhancement This dataset is divided into two parts due to file size constraints. 🔗 Related Datasets: 👉 Part-2 Dataset: Awoal, Robiul (2025), “Mango Leaf Disease Detection Dataset Using Deep Learning - Part 2”, Mendeley Data, V1 Please ensure that both Part-1 & Part-2 are downloaded for full dataset access. 📌 Citation: Awoal, Robiul (2025), “Mango Leaf Disease Detection Dataset Using Deep Learning”, Mendeley Data, V1, doi: 10.17632/sd8hzpg69b.1

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Categories

Artificial Intelligence, Machine Learning, Deep Learning, Agriculture

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