PeachNet: Peach Diseases Detection for Automatic Harvesting

作     者：Wael Alosaimi Hashem Alyami M.Irfan Uddin 

作者机构：Department of Information TechnologyCollege of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer ScienceCollege of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Institute of ComputingKohat University of Science and TechnologyKohat26000Pakistan 

出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)

年 卷 期：2021年第67卷第5期

页      面：1665-1677页

核心收录：

学科分类：1001[医学-基础医学(可授医学、理学学位)] 10[医学] 

基　　金：The authors received funding for this study from Taif University Researchers Supporting Project No.(TURSP-2020/254) Taif University Taif Saudi Arabia 

主　　题：Convolutional neural network computer vision image processing segmentation plant diseases 

摘      要：To meet the food requirements of the seven billion people on Earth,multiple advancements in agriculture and industry have been *** main threat to food items is from diseases and pests which affect the quality and quantity of *** scientific mechanisms have been developed to protect plants and fruits from pests and diseases and to increase the quantity and quality of *** these mechanisms require manual efforts and human expertise to diagnose *** the current decade Artificial Intelligence is used to automate different processes,including agricultural processes,such as automatic *** Learning techniques are becoming popular to process images and identify different *** can use Machine Learning algorithms for disease identification in plants for automatic harvesting that can help us to increase the quantity of the food produced and reduce crop *** this paper,we develop a novel Convolutional Neural Network(CNN)model that can detect diseases in peach plants and *** proposed method can also locate the region of disease and help farmers to find appropriate treatments to protect peach *** the detection of diseases in Peaches VGG-19 architecture is *** the localization of disease regions Mask R-CNN is *** proposed technique is evaluated using different techniques and has demonstrated 94%*** hope that the system can help farmers to increase peach production to meet food demands.