Deep CNN based droplet deposition segmentation for spray distribution assessment-Reference-Cited by-同舟云学术

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Deep CNN based droplet deposition segmentation for spray distribution assessment

Published:2022-09-01 Issue: Volume: Page:
ISSN:
Container-title:2022 27th International Conference on Automation and Computing (ICAC)
language:
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Author:

Chen Tao¹,Meng Yanhua²,Su Jinya³,Liu Cunjia⁴

Affiliation:

1. University of Essex,School of Computer Science and Electronic Engineering,Colchester,U.K

2. Anyang Institute of Technology,School of Mechanical Engineering,Anyang,China

3. University of Aberdeen,Department of Computing Science,Aberdeen,U.K

4. Loughborough University,Department of Aeronautical and Automotive Engineering,Loughborough,U.K

Funder

Science and Technology Facilities Council

Royal Society

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9911058/9911059/09911061.pdf?arnumber=9911061

Reference15 articles.

1. Wheat yellow rust monitoring by learning from multispectral UAV aerial imagery

2. Very deep convolutional networks for large-scale image recognition;simonyan;arXiv preprint arXiv 1409 1556,2014

3. Cbam: Convolutional block attention module;woo;Proceedings of the European Conference on Computer Vision (ECCV),2018

4. U-net: Convolutional networks for biomedical image segmentation;ronneberger;International Conference on Medical Image Computing and Computer-Assisted Intervention,2015

5. Aerial Visual Perception in Smart Farming: Field Study of Wheat Yellow Rust Monitoring

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