{"id":"https://openalex.org/W4380874076","doi":"https://doi.org/10.1145/3591156.3591174","title":"Hurricane Damage Detection using Computer Vision","display_name":"Hurricane Damage Detection using Computer Vision","publication_year":2023,"publication_date":"2023-03-24","ids":{"openalex":"https://openalex.org/W4380874076","doi":"https://doi.org/10.1145/3591156.3591174"},"language":"en","primary_location":{"id":"doi:10.1145/3591156.3591174","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3591156.3591174","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 5th International Conference on Image, Video and Signal Processing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103126123","display_name":"Amrita Ramesh","orcid":"https://orcid.org/0009-0002-9977-5406"},"institutions":[{"id":"https://openalex.org/I196608512","display_name":"PES University","ror":"https://ror.org/05m169e78","country_code":"IN","type":"education","lineage":["https://openalex.org/I196608512"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Amrita Ramesh","raw_affiliation_strings":["PES University, India"],"raw_orcid":"https://orcid.org/0009-0002-9977-5406","affiliations":[{"raw_affiliation_string":"PES University, India","institution_ids":["https://openalex.org/I196608512"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079789935","display_name":"Sanjana K. R. Prasad","orcid":"https://orcid.org/0009-0004-4027-4281"},"institutions":[{"id":"https://openalex.org/I196608512","display_name":"PES University","ror":"https://ror.org/05m169e78","country_code":"IN","type":"education","lineage":["https://openalex.org/I196608512"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sanjana K R Prasad","raw_affiliation_strings":["PES University, India"],"raw_orcid":"https://orcid.org/0009-0004-4027-4281","affiliations":[{"raw_affiliation_string":"PES University, India","institution_ids":["https://openalex.org/I196608512"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005028713","display_name":"Siddhanth Srikanth","orcid":"https://orcid.org/0009-0003-3541-0448"},"institutions":[{"id":"https://openalex.org/I196608512","display_name":"PES University","ror":"https://ror.org/05m169e78","country_code":"IN","type":"education","lineage":["https://openalex.org/I196608512"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Siddhanth Srikanth","raw_affiliation_strings":["PES University, India"],"raw_orcid":"https://orcid.org/0009-0003-3541-0448","affiliations":[{"raw_affiliation_string":"PES University, India","institution_ids":["https://openalex.org/I196608512"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009362621","display_name":"Shikha Tripathi","orcid":"https://orcid.org/0000-0001-8123-5570"},"institutions":[{"id":"https://openalex.org/I196608512","display_name":"PES University","ror":"https://ror.org/05m169e78","country_code":"IN","type":"education","lineage":["https://openalex.org/I196608512"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Shikha Tripathi","raw_affiliation_strings":["PES University, India"],"raw_orcid":"https://orcid.org/0000-0001-8123-5570","affiliations":[{"raw_affiliation_string":"PES University, India","institution_ids":["https://openalex.org/I196608512"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1501,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.46994325,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"126","last_page":"132"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.992900013923645,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.992900013923645,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.9754999876022339,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9388999938964844,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.717507541179657},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.703129768371582},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.6048938035964966},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5957068204879761},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.5031906962394714},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4974401295185089},{"id":"https://openalex.org/keywords/satellite-image","display_name":"Satellite image","score":0.48020562529563904},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.46187543869018555},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.44029393792152405},{"id":"https://openalex.org/keywords/generative-adversarial-network","display_name":"Generative adversarial network","score":0.42242297530174255},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4151146411895752},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.394612580537796},{"id":"https://openalex.org/keywords/satellite","display_name":"Satellite","score":0.3472534418106079},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1570267379283905}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.717507541179657},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.703129768371582},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6048938035964966},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5957068204879761},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5031906962394714},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4974401295185089},{"id":"https://openalex.org/C2985301230","wikidata":"https://www.wikidata.org/wiki/Q725252","display_name":"Satellite image","level":3,"score":0.48020562529563904},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.46187543869018555},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.44029393792152405},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.42242297530174255},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4151146411895752},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.394612580537796},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.3472534418106079},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1570267379283905},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3591156.3591174","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3591156.3591174","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 5th International Conference on Image, Video and Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6899999976158142,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2121616154","https://openalex.org/W2945554431","https://openalex.org/W3027938990","https://openalex.org/W3036103835","https://openalex.org/W3105859057","https://openalex.org/W3124001900","https://openalex.org/W3147506324","https://openalex.org/W3208501207","https://openalex.org/W4210693183","https://openalex.org/W4214895504","https://openalex.org/W4228997907","https://openalex.org/W4281707765","https://openalex.org/W4288020654","https://openalex.org/W4297022962"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W2888032422","https://openalex.org/W4385421777","https://openalex.org/W4377980832","https://openalex.org/W2897769091","https://openalex.org/W2845413374","https://openalex.org/W3005996785","https://openalex.org/W4297411772","https://openalex.org/W4235873501","https://openalex.org/W4392209975"],"abstract_inverted_index":{"Post":[0],"hurricane":[1],"damage":[2,39,46],"assessment":[3],"is":[4,55],"a":[5,88,124],"key":[6],"requirement":[7],"for":[8],"first":[9],"responders":[10],"to":[11,33,56,122],"effectively":[12],"and":[13,47,64,87,110],"accurately":[14],"aid":[15],"in":[16,68],"disaster":[17],"recovery.":[18],"This":[19],"paper":[20],"focuses":[21],"on":[22],"the":[23,58,70,75,95,120],"use":[24],"of":[25,28,38,52,91],"satellite":[26,71],"imagery":[27],"buildings":[29],"across":[30],"an":[31],"area,":[32],"identify":[34],"four":[35],"different":[36],"degrees":[37],"-":[40],"no":[41],"damage,":[42,44],"minor":[43],"major":[45],"destroyed.":[48],"The":[49,102],"main":[50],"contribution":[51],"this":[53],"work":[54],"explore":[57],"state-of-the-art":[59],"Vision":[60,96],"Transformer":[61,97],"(ViT)":[62],"architecture,":[63],"analyse":[65],"its":[66],"efficacy":[67],"classifying":[69],"image":[72,108],"dataset":[73],"into":[74],"above-mentioned":[76],"classes.":[77],"Various":[78],"Convolutional":[79],"Neural":[80],"Networks":[81],"(CNNs)":[82],"have":[83,106],"also":[84],"been":[85,99],"trained,":[86],"comparative":[89],"analysis":[90],"these":[92],"architectures":[93],"with":[94],"has":[98],"carried":[100],"out.":[101],"reported":[103],"existing":[104],"techniques":[105],"utilized":[107],"pre-processing":[109],"data":[111],"augmentation":[112],"using":[113],"Generative":[114],"Adversarial":[115],"Networks.":[116],"ViT":[117],"successfully":[118],"outperformed":[119],"CNNs,":[121],"give":[123],"higher":[125],"accuracy.":[126]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
