Training and Performance Analysis of Vehicle Detection Neural Networks to Field Test and Simulation Datasets of Multi-channel Lidar-Reference-Cited by-同舟云学术

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Training and Performance Analysis of Vehicle Detection Neural Networks to Field Test and Simulation Datasets of Multi-channel Lidar

Published:2021-12-02 Issue:12 Volume:29 Page:1123-1132
ISSN:1225-6382
Container-title:Transaction of the Korean Society of Automotive Engineers
language:en
Short-container-title:KSAE

Author:

Kim Yunbeom,Lee Taehyun,Song Bongsob

Funder

Ministry of Trade, Industry and Energy

Ministry of Land, Infrastructure and Transport

Publisher

The Korean Society of Automotive Engineers

Subject

Automotive Engineering

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Development of Infrastructure Lidar Real-time Background Removal Algorithm;Transaction of the Korean Society of Automotive Engineers;2023-12-01

2. Performance Improvement of Deep Learning Object Detection Method Using Dynamic Occupancy Grid Map;Transaction of the Korean Society of Automotive Engineers;2022-10-01

3. Maneuver Classification of Lane Change Based on Roadside Sensors Using Field Operational Test Data;Transaction of the Korean Society of Automotive Engineers;2022-10-01

4. A Study on Deep Learning Based Lidar Object Detection Neural Networks for Autonomous Driving;Transaction of the Korean Society of Automotive Engineers;2022-08-01

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