首页> 外文会议>2016 International Conference on Global Trends in Signal Processing, Information Computing and Communication >Fusion classification technique used to detect downy and Powdery Mildew grape leaf diseases
【24h】

Fusion classification technique used to detect downy and Powdery Mildew grape leaf diseases

机译:用于检测霜霉病和白粉病葡萄叶病的融合分类技术

获取原文
获取原文并翻译 | 示例

摘要

Grape constitutes one of the most widely grown fruit crop in the India. Manual observation of experts is used in practice for detection of leaf diseases, which takes more time for further control action. Without accurate disease diagnosis, proper control actions cannot be taken at appropriate time. This is where modern agriculture technique is required to detect and prevent the leaf from different diseases. This paper aims to introduce a new approach for detection of grape leaf diseases using image processing, which will minimize the loss and increase its profit due to automation. In this system, classification is done using Support Vector Machine (SVM) and Artificial Neural Network (ANN) classifies separately. A new classifier is proposed using fusion classification technique which ensembles classifiers from SVM and ANN to regenerate base classifier for grape leaf disease detection. Based on detection of disease the proper mixture of fungicides will be provided to the grape farmers.
机译:葡萄是印度最广泛种植的水果作物之一。在实践中,使用专家的手动观察来检测叶病,这需要更多时间才能采取进一步的控制措施。没有准确的疾病诊断,就无法在适当的时间采取适当的控制措施。这是需要现代农业技术来检测和预防叶片不同疾病的地方。本文旨在介绍一种使用图像处理技术检测葡萄叶病的新方法,该方法将最大程度地减少损失并提高自动化带来的利润。在该系统中,使用支持向量机(SVM)和人工神经网络(ANN)分别进行分类。提出了一种融合融合分类技术的新分类器,该方法融合了支持向量机和人工神经网络的分类器,以重新生成用于葡萄叶病检测的基本分类器。基于疾病的检测,将向葡萄种植者提供适当的杀菌剂混合物。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号