Detection and Semantic Segmentation of Disaster Damage in UAV Footage-Reference-Cited by-同舟云学术

Detection and Semantic Segmentation of Disaster Damage in UAV Footage

Published:2021-03 Issue:2 Volume:35 Page:04020063
ISSN:0887-3801
Container-title:Journal of Computing in Civil Engineering
language:en
Short-container-title:J. Comput. Civ. Eng.

Author:

Pi Yalong¹,Nath Nipun D.²,Behzadan Amir H.³

Affiliation:

1. Ph.D. Candidate, Dept. of Construction Science, Texas A&M Univ., 3137 TAMU, College Station, TX 77843.

2. Ph.D. Student, Zachry Dept. of Civil Engineering, Texas A&M Univ., 3136 TAMU, College Station, TX 77843.

3. Clark Construction Endowed Associate Professor, Dept. of Construction Science, Texas A&M Univ., 3137 TAMU, College Station, TX 77843 (corresponding author).

Publisher

American Society of Civil Engineers (ASCE)

Subject

Computer Science Applications,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29CP.1943-5487.0000947

Reference60 articles.

1. American Red Cross. 2019. “American red cross damage assessment.” Accessed June 15 2020. http://www.resiliencenw.org/2012files/LongTermRecovery/DisasterAssessmentWorkshop.pdf.

2. SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

3. Bhatt P. S. Sarangi and S. Pappula. 2018. “Coarse clustering and classification of images with CNN features for participatory sensing in agriculture.” In Proc. Int. Conf. on Pattern Recognition Applications and Methods 488–495. Funchal Portugal: Springer. https://doi.org/10.5220/0006648504880495.

4. Birds Eye UAS. 2018. “Hurricane Michael St Joe Beach FL.” YouTube. Accessed April 1 2020. https://www.youtube.com/watch?v=9nLpGrpCP3o.

5. Chen M. and J. Li. 2019. “Deep convolutional neural network application on rooftop detection for aerial image.” Preprint submitted April 21 2020. http://arxiv.org/abs/1910.13509.

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