Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/6898
AuthorsPacifici, Fabio* 
Chini, Marco* 
Bignami, Christian* 
Stramondo, Salvatore* 
Emery, William J.* 
TitleAUTOMATIC DAMAGE DETECTION USING PULSE-COUPLED NEURAL NETWORKS FOR THE 2009 ITALIAN EARTHQUAKE
Issue DateJul-2010
URIhttp://hdl.handle.net/2122/6898
Keywordsneural networks
damage detection
AbstractIn this paper, we investigate the performance of pulse-coupled neural networks (PCNNs) to detect the damage caused by an earthquake. PCNN is an unsupervised model in the sense that it does not need to be trained, which makes it an operational tool during crisis events when it is crucial to produce damage maps as soon as the post-event images are available. The damage map resulting from PCNN was validated at a block scale of 120x120m using ground truth obtained by a combination of ground survey and visual inspection of the before- and after-event images. The comparison showed agreement between the change measured by PCNN on block scale and the damage occurred.
Appears in Collections:Conference materials

Files in This Item:
File Description SizeFormat 
Pacifici2_et_al_final.pdf255.77 kBAdobe PDFView/Open
Show full item record

Page view(s)

70
Last Week
0
Last month
checked on Jun 27, 2017

Download(s)

21
checked on Jun 27, 2017

Google ScholarTM

Check