2026-10-11T23:45:21Z https://data.mendeley.com/oai

oai:data.mendeley.com/t9hgvk2h9p.1 2025-06-30T17:34:33Z

Ripon, Shamim Cotton Leaf Image Dataset for Disease Classification Mendeley Data This dataset comprises high-resolution images of cotton leaves categorized by disease type and health condition. It is structured into two parts: the Original Dataset and the Augmented Dataset. Original Dataset The original set contains real-world images of cotton leaves affected by various diseases, alongside healthy specimens. The images are labeled into the following five classes: - Alternaria Leaf Spot: 173 images - Bacterial Blight: 218 images - Fusarium Wilt: 337 images - Healthy Leaf: 333 images - Verticillium Wilt: 312 images Augmented Dataset To enhance diversity and improve model robustness, data augmentation techniques were applied to the original images. The resulting augmented dataset includes: - aug_Alternaria_Leaf: 987 images - aug_Bacterial_Blight: 1027 images - aug_Fusarium_Wilt: 957 images - aug_Healthy_Leaf: 1015 images - aug_Verticillium_Wilt: 977 images This dataset is well-suited for research in plant pathology, machine learning, and image classification tasks related to agriculture and crop health monitoring. Computer Vision Image Classification Agriculture Gani , Raiyan Niha, Nazratan Mazumder Rahat, Wasimul Bari Toufiq, Shafaeat Hasan Maisha, Mushfida Ferdous Ahmed, Jubaer Dataset doi:10.17632/t9hgvk2h9p.1 oai:data.mendeley.com/t9hgvk2h9p.1 Creative Commons Attribution 4.0 International http://creativecommons.org/licenses/by/4.0 https://data.mendeley.com/datasets/t9hgvk2h9p 2025-06-30T17:34:33Z