2026-10-16T16:41:05Z https://data.mendeley.com/oai

oai:data.mendeley.com/f35jp46gms.1 2025-03-17T16:20:19Z

Nayeem, Rejowan Arifin Carambola Leaf & Fruit Dataset for Disease Detection and Classification Mendeley Data This dataset is designed for the detection and classification of diseases affecting carambola (starfruit) leaves and fruits using image-based analysis. Captured using a smartphone, it consists of high-quality images covering both healthy and diseased samples. The dataset can be utilized for training deep learning models in plant disease detection, classification, and agricultural monitoring applications. Original Dataset: - Number of images: 2,618 - Data format: .jpg Processed Dataset: - Number of images: 2,618 - Data format: .jpg Augmented Dataset: - Number of images: 15,000 - Data format: .jpg Augmentation Techniques: 1.Rotation, 2. Flipping, 3. Brightening, 4. Contrast Adjustment, 5. Blurring, 6. Shearing, 7. Zooming, 8. Adding Noise Applications: - This dataset can be used for plant disease detection and classification, enabling agricultural monitoring using AI-based models. - It supports image-based plant health assessment and can be applied in precision farming and crop management. - It can be used to train deep learning models for improved disease detection and classification accuracy. Agricultural Science Artificial Intelligence Computer Vision Machine Learning Sustainable Agriculture Deep Learning Muhib, S.M. Abdullah Al Mezi, Noman Emon, Nafiz Ahmed Dataset doi:10.17632/f35jp46gms.1 oai:data.mendeley.com/f35jp46gms.1 Creative Commons Attribution 4.0 International http://creativecommons.org/licenses/by/4.0 https://data.mendeley.com/datasets/f35jp46gms 2025-03-17T16:20:19Z