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Shane Crawford

The University of Alabama

SCHOLARLY PAPERS

3

DOWNLOADS

145

TOTAL CITATIONS

0

Scholarly Papers (3)

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1.

Do Housing Prices Change with Building Codes? *

Number of pages: 27
Lars Powell, Sebastain Awondo and Shane Crawford
University of Alabama - Culverhouse College of Commerce & Business Administration, University of Alabama - Culverhouse College of Commerce & Business Administration and The University of Alabama
Downloads 97

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R31, R32, R38 Building Codes, House Prices, Real Estate

2.

What Really Matters for Automated Tornado Damage Assessment? Evidence from 2,300 Experiments Across 79 Open-Source Architectures with Cross-Event Generalization

Number of pages: 49 Posted: 09 Mar 2026
Robinson Umeike, Thang Dao, Shane Crawford, John W. van de Lindt, Blythe Johnston, Wanting (Lisa) Wang, Trung Do, Ajibola Mofikoya, Sarbesh Banjara and Cuong Pham
The University of Alabama, University of Alabama, The University of Alabama, affiliation not provided to SSRN, Government of the United States of America - Argonne National Laboratory, Old Dominion University, University of South Alabama, The University of Alabama, The University of Alabama and University of South Alabama
Downloads 35 (1,332,057)

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Deep Learning, Automated Damage Assessment, Vision transformers, Convolutional Neural Networks, Cross-Event Generalisation, Disaster Management

3.

TornadoNet: Real-Time Building Damage Detection with Ordinal Supervision

Number of pages: 33 Posted: 27 Apr 2026
Robinson Umeike, Cuong Pham, Ryan Hausen, Thang Dao, Shane Crawford, Tanya Brown-Giammanco, Gerard Lemson, John W. van de Lindt, Blythe Johnston, Arik Mitschang and Trung Do
The University of Alabama, University of South Alabama, Johns Hopkins University, University of Alabama, The University of Alabama, Government of the United States of America - National Institute of Standards and Technology, Johns Hopkins University Institute of Data Intensive Engineering and Science, affiliation not provided to SSRN, affiliation not provided to SSRN, Johns Hopkins University and University of South Alabama
Downloads 13 (1,541,665)

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Post-disaster Damage Assessment, Building damage detection, Ordinal Classification, object detection, Deep learning, Disaster resilience