Neural network‐based semantic segmentation model for robot perception of driverless vision-Reference-Cited by-同舟云学术

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Neural network‐based semantic segmentation model for robot perception of driverless vision

Published:2020-11-10 Issue:4 Volume:2 Page:190-196
ISSN:2631-6315
Container-title:IET Cyber-Systems and Robotics
language:en
Short-container-title:IET cyber-systems robotics

Author:

Ye Lu¹²,Duan Ting²,Zhu Jiayi²

Affiliation:

1. School of Information and Electronic Engineering Zhejiang University of Science & Technology Hangzhou Zhejiang People's Republic of China

2. School of Mechanical and Energy Engineering Zhejiang University of Science & Technology Hangzhou Zhejiang People's Republic of China

Publisher

Institution of Engineering and Technology (IET)

Subject

General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-csr.2020.0040

Reference30 articles.

1. Deep Learning for Driverless Vehicles

2. SinghR.SalujaD.KumarS.: ‘Power controlled adaptive range radar for self driving vehicles’.2019 IEEE 89th Vehicular Technology Conf. (VTC2019‐Spring) Kuala Lumpur Malaysia April2019 pp.1–4

3. VincentO.R.FolorunsoO.: ‘A descriptive algorithm for Sobel image edge detection’.Proc. Informing Science & IT Education Conf. Macon USA June2009 pp.97–107

4. BeetzM.Bálint‐BenczédiF.BlodowN.et al.: ‘Robosherlock: unstructured information processing for robot perception’.2015 IEEE Int. Conf. on Robotics and Automation (ICRA) Seattle Washington May2015 pp.1549–1556

5. SchopsT.SattlerT.PollefeysM.: ‘Bad SLAM: bundle adjusted direct RGB‐D slam’.Proc. IEEE Conf. on Computer Vision and Pattern Recognition Long Beach CA June2019 pp.134–144

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