Evolutionary Feature Optimization for Plant Leaf Disease Detection by Deep Neural Networks for Apple Leaf
作者: Jalal Sadoon Hameed AlbayatiBurak Berk Üstündağ
刊名: International Journal of Computational Intelligence Systems, 2020
来源数据库: Atlantis Press
DOI: 10.2991/ijcis.d.200108.001
原始语种摘要: Apple leaf disease is the foremost factor that restricts apple yield and quality. Usually, much time is taken for disease detection with the existing diagnostic techniques; therefore, farmers frequently miss the best time for preventing and treating diseases. The detection of apple leaf diseases is a significant research problem, and its main aim is to discover an efficient technique for disease leaf image diagnosis. This article has made an effort to propose a method that can detect the disease of apple plant leaf using deep neural network (DNN). Plant diseases detection system (PDDS) architecture is designed. Speeded up robust feature (SURF) is used for feature extraction and Grasshopper Optimization Algorithm (GOA) for feature optimization, which helps to achieve better detection and...
全文获取路径: Atlantis出版社  (合作)
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关键词翻译
关键词翻译
  • feature 结构元件
  • propose 提议
  • existing 现行
  • efficient 有用的
  • effectiveness 有效性
  • technique 技术
  • achieve 达到
  • robust 牢固的
  • apple 苹果
  • optimization 最佳化