Target Detection for Construction Machinery Based on Deep Learning and Multisource Data Fusion-Reference-Cited by-同舟云学术

Target Detection for Construction Machinery Based on Deep Learning and Multisource Data Fusion

Published:2023-05-15 Issue:10 Volume:23 Page:11070-11081
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Wang Yong¹^ORCID,Liu Xinhui¹^ORCID,Zhao Quanxiao¹^ORCID,He Haiteng¹^ORCID,Yao Zongwei²^ORCID

Affiliation:

1. School of Mechanical and Aerospace Engineering, Jilin University, Changchun, Jilin, China

2. Key Laboratory of CNC Equipment Reliability, Ministry of Education, School of Mechanical and Aerospace Engineering, Jilin University, Changchun, Jilin, China

Funder

National Natural Science Foundation of China

Science and Technology Research Project of Jilin Provincial Education Department

Natural Science Foundation of Jilin Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/7361/10124342/10098769.pdf?arnumber=10098769

Reference37 articles.

1. Posting Techniques in Indoor Environments Based on Deep Learning for Intelligent Building Lighting System

2. Efficient Online Segmentation for Sparse 3D Laser Scans

3. MobileNetV2: Inverted Residuals and Linear Bottlenecks

4. Application of Ground-Penetrating Radar for Detecting Internal Anomalies in Tree Trunks with Irregular Contours

5. Region-Based Convolutional Networks for Accurate Object Detection and Segmentation

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