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precise agriculture:Effective Deep Learning Strategies to Detect Pest Insects

IEEE/CAA Journal of Automatica Sinica 2022年第2期9卷 246-258页

作者： Luca Butera Alberto Ferrante Mauro Jermini Mauro Prevostini Cesare Alippi Universitàdella Svizzera italiana Faculty of InformaticsLugano 6900Switzerland Agroscope Research Centre CadenazzoCadenazzo 6594Switzerland IEEE

Pest insect monitoring and control is crucial to ensure a safe and profitable crop growth in all plantation types,as well as guarantee food quality and limited use of *** aim at extending traditional monitoring by means of traps,by involving the general public in reporting the presence of insects by using *** includes the largely unexplored problem of detecting insects in images that are taken in noncontrolled ***,pest insects are,in many cases,extremely similar to other species that are ***,computer vision algorithms must not be fooled by these similar insects,not to raise unmotivated *** this work,we study the capabilities of state-of-the-art(SoA)object detection models based on convolutional neural networks(CNN)for the task of detecting beetle-like pest insects on nonhomogeneous images taken outdoors by different ***,we focus on disambiguating a pest insect from similar harmless *** consider not only detection performance of different models,but also required computational *** study aims at providing a baseline model for this kind of *** results show the suitability of current SoA models for this application,highlighting how FasterRCNN with a MobileNetV3 backbone is a particularly good starting point for accuracy and inference execution *** combination provided a mean average precision score of 92.66%that can be considered qualitatively at least as good as the score obtained by other authors that adopted more specific models.

关键词： Computer vision machine learning neural network pest insect pest monitoring Popillia japonica precise agriculture

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CASE STUDY OF DIGITAL agriculture IN THE OUTSKIRTS OF BEIJING

CASE STUDY OF DIGITAL AGRICULTURE IN THE OUTSKIRTS OF BEIJIN...

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The 3rd International Symposium on Intelligent Information Technology in agriculture(ISIITA)

作者： Yang Zhang Tieying Xue Beijing Vocational College of agriculture Beijing 102442 China

＜正＞This article focuses on digital agriculture case study in the districts of Mentougou and Tongzhou by analyzing the current situation and points out the necessity of some basic tasks.

关键词： Digital agriculture(DA) Remote Sensing(RS) precise agriculture precise Data Geographical Information System(GIS) Global Positioning System(GPS)

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