Cost-sensitive stacked sparse auto-encoder models to detect striped stem borer infestation on rice based on hyperspectral imaging-Reference-Cited by-同舟云学术

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Cost-sensitive stacked sparse auto-encoder models to detect striped stem borer infestation on rice based on hyperspectral imaging

Published:2019-03 Issue: Volume:168 Page:49-58
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Fan Yangyang,Zhang Chu,Liu Ziyi,Qiu Zhengjun,He Yong

Funder

China National Key Research and Development Program

China Postdoctoral Science Foundation

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference35 articles.

1. Expression of the maize proteinase inhibitor (mpi) gene in rice plants enhances resistance against the striped stem borer (Chilo suppressalis): effects on larval growth and insect gut proteinases;Vila;Plant Biotechnol. J.,2010

2. Study of silicon effects on plant growth and resistance to stem borer in rice;Hosseini;Commun. Soil Sci. Plant Anal.,2012

3. Ecology of common insect pests of rice;Pathak;Annu. Rev. Entomol.,1968

4. Improved classification accuracy of powdery mildew infection levels of wine grapes by spatial-spectral analysis of hyperspectral images;Knauer;Plant Methods,2017

5. Mechanisms of plant defense against insect herbivores;War;Plant Signal. Behav.,2012

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