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  • 标题:An effective identification of crop diseases using faster region based convolutional neural network and expert systems
  • 本地全文:下载
  • 作者:P. Chandana ; G. S. Pradeep Ghantasala ; J. Rethna Virgil Jeny
  • 期刊名称:International Journal of Electrical and Computer Engineering
  • 电子版ISSN:2088-8708
  • 出版年度:2020
  • 卷号:10
  • 期号:6
  • 页码:6531-6540
  • DOI:10.11591/ijece.v10i6.pp6531-6540
  • 出版社:Institute of Advanced Engineering and Science (IAES)
  • 摘要:The majority of research Study is moving towards cognitive computing, ubiquitous computing, internet of things (IoT) which focus on some of the real time applications like smart cities, smart agriculture, wearable smart devices. The objective of the research in this paper is to integrate the image processing strategies to the smart agriculture techniques to help the farmers to use the latest innovations of technology in order to resolve the issues of crops like infections or diseases to their crops which may be due to bugs or due to climatic conditions or may be due to soil consistency. As IoT is playing a crucial role in smart agriculture, the concept of infection recognition using object recognition the image processing strategy can help out the farmers greatly without making them to learn much about the technology and also helps them to sort out the issues with respect to crop. In this paper, an attempt of integrating kissan application with expert systems and image processing is made in order to help the farmers to have an immediate solution for the problem identified in a crop.
  • 关键词:Cognitive Computing;IOT;Image Processing;Object Recognition;Smart Agriculture
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