Show simple item record

contributor authorKim, Jooho
contributor authorKanumuri, Ruthvik
contributor authorHatzis, Joshua J.
contributor authorPark, Sunyoung
contributor authorCampbell, Patrick A.
contributor authorCalhoun, Kristin M.
date accessioned2026-08-20T21:09:15Z
date available2026-08-20T21:09:15Z
date copyright2026/06/08
date issued2026
identifier otherNHREFO.NHENG-2701.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314035
description abstractAbstractAccurate assessment of tornado impacts requires detailed information on building characteristics that influence vulnerability. This study investigates a convolutional neural network (CNN)-based approach to classify nonresidential buildings into ...Practical ApplicationsThis study shows how street-level imagery can be used to build a more detailed and up-to-date building inventory focused on commercial and industrial structure, which are often limited or generalized in national data sets such as ...
publisherAmerican Society of Civil Engineers
titleCNN-Based Building Type Classification into EF Scale Categories to Support Tornado Damage Assessments
typeJournal Article
journal volume27
journal issue3
journal titleNatural Hazards Review
identifier doi10.1061/NHREFO.NHENG-2701
journal fristpage04026018-1
journal lastpage04026018-18
page18
treeNatural Hazards Review:;2026:;Volume ( 027 ):;issue: 003
contenttypeFulltext


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record