MDANet: Multi-scale Vague Boundary Augmented Dual Attention Network for Semantic Segmentation of Outdoor Plants-Reference-Cited by-同舟云学术

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MDANet: Multi-scale Vague Boundary Augmented Dual Attention Network for Semantic Segmentation of Outdoor Plants

Published:2023-07-17 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Real-time Computing and Robotics (RCAR)
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Author:

Yuan Pengfei¹,Wu Hongmin²,Zhu Zhihan¹,Mao Shixin³,Zhou Xuefeng²,Zhu Haifei¹

Affiliation:

1. Guangdong University of Technology,Biomimetic and Intelligent Robotics Lab (BIRL),Guangzhou,China,510006

2. Institute of Intelligent Manufacturing, Guangdong Academy of Sciences,Guangdong Key Laboratory of Modern Control Technology,Guangzhou,China,510070

3. Jiutian Innovation (Guangdong) Intelligent Technology Co., Ltd,Foshan,Guangdong,China,528299

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10249208/10249018/10249393.pdf?arnumber=10249393

Reference23 articles.

1. Vegetation Detection Using Deep Learning and Conventional Methods

2. Tree, Shrub, and Grass Classification Using Only RGB Images

3. CCNet: Criss-Cross Attention for Semantic Segmentation

4. Multi-scale context aggregation by dilated convolutions;yu,2015

5. Semantic segmentation for plant phenotyping using advanced deep learning pipelines

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