A Training Dataset for Deep Neural Network Model Recognition of Common Cotton Diseases

A Training Dataset for Deep Neural Network Model Recognition of Common Cotton Diseases provides strong support for cotton disease monitoring and prevention and control. This dataset contains images of cotton plants under different disease states, covering five phenotypic state images of cotton plants, including anthracnose, bacterial angular spot, brown spot, wilt, and health. A total of 816 images of cotton with anthracnose, 919 images of bacterial angular spot, 917 images of brown spot, 538 images of fusarium wilt, and 264 images of healthy status were collected. The images under each disease state have corresponding file name prefixes for easy data retrieval and use.

面向常见棉花病害识别的深度神经网络（Deep Neural Network）模型训练数据集，为棉花病害监测与防控提供了有力支撑。本数据集包含不同病害状态下的棉花植株图像，涵盖棉花植株的五类表型状态图像，分别为炭疽病（anthracnose）、细菌性角斑病（bacterial angular spot）、褐斑病（brown spot）、镰刀菌枯萎病（fusarium wilt）以及健康状态。本次数据集共收集到炭疽病侵染棉株图像816张、细菌性角斑病图像919张、褐斑病图像917张、镰刀菌枯萎病图像538张以及健康棉株图像264张。各病害状态下的图像均配有对应的文件名前缀，便于数据检索与使用。

搜集汇总

背景与挑战

背景概述

该数据集是一个用于深度神经网络模型识别常见棉花病害的训练数据集，包含3454张棉花植物图像，覆盖五种表型状态：炭疽病（816张）、细菌性角斑病（919张）、褐斑病（917张）、枯萎病（538张）和健康状态（264张），旨在支持棉花病害的监测和防控研究。数据集总大小为2.74 GB，发布于2024年，适用于农学和计算机科学领域的应用。