Evaluating the Influence of UAV Flight Characteristics on the Detection of Objects in Photogrammetric Models Using Deep Neural Networks-Reference-Cited by-同舟云学术

Evaluating the Influence of UAV Flight Characteristics on the Detection of Objects in Photogrammetric Models Using Deep Neural Networks

Published:2022-08-31 Issue: Volume: Page:
ISSN:
Container-title:International Conference on Transportation and Development 2022
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Author:

Congress Surya Sarat Chandra¹²³,Gajurel Amit¹²³,Puppala Anand J.¹²³

Affiliation:

1. Senior Research Engineer, Zachry Dept. of Civil and Environmental Engineering, Texas A&M Univ., College Station, TX.

2. Doctoral Student, Zachry Dept. of Civil and Environmental Engineering, Texas A&M Univ., College Station, TX.

3. A.P. and Florence Wiley Chair Professor, Zachry Dept. of Civil and Environmental Engineering, Texas A&M Univ., College Station, TX.

Publisher

American Society of Civil Engineers

Link

https://ascelibrary.org/doi/pdf/10.1061/9780784484371.014

Reference26 articles.

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4. Bone E. and Bolkcom C. 2003. Unmanned aerial vehicles: Background and issues for congress. Library of Congress Washington DC Congressional Research Service.

5. Cheng B. Wei Y. Shi H. Feris R. Xiong J. and Huang T. 2018. “Revisiting rcnn: On awakening the classification power of faster rcnn.” Proceedings of the European conference on computer vision (ECCV) 453–468.

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