Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/443936
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DC FieldValueLanguage
dc.coverage.spatial
dc.date.accessioned2023-01-12T10:23:19Z-
dc.date.available2023-01-12T10:23:19Z-
dc.identifier.urihttp://hdl.handle.net/10603/443936-
dc.description.abstractHurricanes or tropical cyclones are one of the most calamitous natural disasters occurring newlineon earth. They are accompanied by heavy rainfall, floods, and very high-speed winds at the newlinerate of 200 miles/hour causing excessive damage to property and human casualties. When newlinea hurricane occurs, it is essential to assess the damage for providing relief instantly to the newlineaffected people. The extent of damage could be found by analyzing flooded /damaged newlinebuildings. Earlier this was done through a ground survey which was a tedious task. newlineImmediate steps need to be taken and social media platforms like Twitter help to provide newlinerelief to the affected public. However, it is difficult to analyze high-volume data obtained newlinefrom social media posts. Therefore the efficiency and accuracy of useful data extracted newlinefrom the enormous posts related to disasters are low. newline
dc.format.extent
dc.languageHindi
dc.relation
dc.rightsuniversity
dc.titleHurricane Damage Detection from Satellite Imagery using Deep Learning
dc.title.alternative
dc.creator.researcherSwapandeep Kaur
dc.subject.keywordEngineering
dc.subject.keywordEngineering and Technology
dc.subject.keywordEngineering Electrical and Electronic
dc.description.note
dc.contributor.guideSheifali Gupta and Swati Singh
dc.publisher.placeChandigarh
dc.publisher.universityChitkara University, Punjab
dc.publisher.institutionFaculty of Electronics
dc.date.registered2019
dc.date.completed2022
dc.date.awarded2022
dc.format.dimensions
dc.format.accompanyingmaterialDVD
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Electronics

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80_recommendation.pdfAttached File141.75 kBAdobe PDFView/Open
abstract.pdf91.23 kBAdobe PDFView/Open
annexures.pdf167.02 kBAdobe PDFView/Open
chapter 1.pdf770.61 kBAdobe PDFView/Open
chapter 2.pdf219.29 kBAdobe PDFView/Open
chapter 3.pdf337.85 kBAdobe PDFView/Open
chapter 4.pdf1.82 MBAdobe PDFView/Open
chapter 5.pdf785.91 kBAdobe PDFView/Open
chapter 6.pdf1.3 MBAdobe PDFView/Open
chapter 7.pdf379.22 kBAdobe PDFView/Open
contents.pdf61.28 kBAdobe PDFView/Open
preliminary pages.pdf236.01 kBAdobe PDFView/Open
title.pdf9.22 kBAdobe PDFView/Open


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