A fully convolutional network for weed mapping of unmanned aerial vehicle (UAV) imagery-Reference-Cited by-同舟云学术

A fully convolutional network for weed mapping of unmanned aerial vehicle (UAV) imagery

Published:2018-04-26 Issue:4 Volume:13 Page:e0196302
ISSN:1932-6203
Container-title:PLOS ONE
language:en
Short-container-title:PLoS ONE

Author:

Huang Huasheng^ORCID,Deng Jizhong,Lan Yubin,Yang Aqing,Deng Xiaoling,Zhang Lei

Funder

Science and Technology Planning Project of Guangdong Province, China

the National Key Research and Development Plan: High Efficient Ground and Aerial Spraying Technology and Intelligent Equipment, China

The National Natural Science Fund, China

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

Reference33 articles.

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3. Current status and future directions of precision aerial application for site-specific crop management in the USA;Y Lan;COMPUT ELECTRON AGR,2010

4. Detecting Late-Season Weed Infestations in Soybean (Glycine max)1;CH KOGER;WEED TECHNOL,2003

5. Airborne multi-spectral imagery for mapping cruciferous weeds in cereal and legume crops;A Castro;Precision Agric,2012

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