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Coffee Leaf Rust Dataset | IEEE DataPort
Three month Coffee Leaf Rust dataset generated by the Cyber Physical Data Collection System
Coffee Leaf Rust Dataset - GitHub
Three month Coffee Leaf Rust dataset Contribute to dvelaren clr-dataset development by creating an account on GitHub
A Machine Learning Dataset for Classification of Common Coffee Leaf . . .
This dataset provides a well-structured collection of 3,312 labeled images of coffee leaves captured from farms in Uganda The images are categorized into three main classes: Healthy, Coffee Leaf Rust , and Phoma disease
RoCoLe - Dataset Ninja
This dataset encompasses images of both the upper and back sides of coffee leaves collected from robusta coffee crops, representing various states (healthy and unhealthy), the presence of diseases (rust and red_spider_mite), and varying levels of infection severity
RoCoLe: A robusta coffee leaf images dataset for evaluation of machine . . .
In this article we introduce a robusta coffee leaf images dataset called RoCoLe The dataset contains 1560 leaf images with visible red mites and spots (denoting coffee leaf rust presence) for infection cases and images without such structures for healthy cases
Coffee Leaf Disease Detection – AI Machine Learning Dataset
Download the RoCoLe Robusta Coffee Leaf Image Dataset, featuring 1,560 high-quality images categorized into Healthy, Coffee Rust disease, and Spider Mite infestation
Coffee Leaf Rust Disease Detection and Implementation of an Edge Device . . .
Therefore, detecting coffee leaf rust is important to support the decision on pruning infected leaves The dataset was acquired from a coffee farm in Majalengka Regency, Indonesia Only
Coffee Leaf Rust Disease Detection and Implementation of an Edge Device . . .
Therefore, detecting coffee leaf rust is important to support the decision on pruning infected leaves The dataset was acquired from a coffee farm in Majalengka Regency, Indonesia Only images with clearly visible spots of coffee leaf rust were selected
COFFEE LEAF DISEASE IMAGE CLASSIFICATION - GitHub
The dataset contains leaf images which were collected from Arabica coffee type and it shows three sets of Phoma, Rust and Cescospora images and one set of healthy images
Early Detection of Coffee Leaf Rust Through Convolutional Neural . . .
To overcome these barriers, we propose a preprocessing technique that involves convolving training images with a high-pass filter to enhance lesion-leaf contrast, significantly improving model efficacy in resource-limited environments