{"id":"https://openalex.org/W4313130695","doi":"https://doi.org/10.1145/3549206.3549212","title":"Identification of undamaged buildings after the event of disaster using Deep Learning","display_name":"Identification of undamaged buildings after the event of disaster using Deep Learning","publication_year":2022,"publication_date":"2022-08-04","ids":{"openalex":"https://openalex.org/W4313130695","doi":"https://doi.org/10.1145/3549206.3549212"},"language":"en","primary_location":{"id":"doi:10.1145/3549206.3549212","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3549206.3549212","pdf_url":null,"source":{"id":"https://openalex.org/S4363609025","display_name":"Proceedings of the 2022 Fourteenth International Conference on Contemporary Computing","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 Fourteenth International Conference on Contemporary Computing","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/A5079823175","display_name":"Neha Tyagi","orcid":"https://orcid.org/0000-0001-8040-1661"},"institutions":[{"id":"https://openalex.org/I154970844","display_name":"Jaypee Institute of Information Technology","ror":"https://ror.org/05sttyy11","country_code":"IN","type":"education","lineage":["https://openalex.org/I154970844"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Neha Tyagi","raw_affiliation_strings":["Department of Computer Science & Engineering and Information Technology, Jaypee Institute of Information Technology, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering and Information Technology, Jaypee Institute of Information Technology, India","institution_ids":["https://openalex.org/I154970844"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015706894","display_name":"Mukesh Saraswat","orcid":"https://orcid.org/0000-0002-3427-9105"},"institutions":[{"id":"https://openalex.org/I154970844","display_name":"Jaypee Institute of Information Technology","ror":"https://ror.org/05sttyy11","country_code":"IN","type":"education","lineage":["https://openalex.org/I154970844"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Mukesh Saraswat","raw_affiliation_strings":["Department of Computer Science & Engineering and Information Technology, Jaypee Institute of Information Technology, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering and Information Technology, Jaypee Institute of Information Technology, India","institution_ids":["https://openalex.org/I154970844"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5079823175"],"corresponding_institution_ids":["https://openalex.org/I154970844"],"apc_list":null,"apc_paid":null,"fwci":0.2397,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.52309846,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"27","last_page":"31"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9937999844551086,"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":0.9937999844551086,"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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9865000247955322,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"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/T12597","display_name":"Fire Detection and Safety Systems","score":0.986299991607666,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.9019572734832764},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7871037721633911},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6299082040786743},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6013919115066528},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5614303946495056},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.4903290569782257},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4864051640033722},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.472896009683609},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.43901607394218445},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.43830594420433044},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3990292549133301},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33557260036468506},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.28851526975631714}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.9019572734832764},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7871037721633911},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6299082040786743},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6013919115066528},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5614303946495056},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.4903290569782257},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4864051640033722},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.472896009683609},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.43901607394218445},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.43830594420433044},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3990292549133301},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33557260036468506},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.28851526975631714},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3549206.3549212","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3549206.3549212","pdf_url":null,"source":{"id":"https://openalex.org/S4363609025","display_name":"Proceedings of the 2022 Fourteenth International Conference on Contemporary Computing","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 Fourteenth International Conference on Contemporary Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Climate action","id":"https://metadata.un.org/sdg/13","score":0.6800000071525574}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W57444138","https://openalex.org/W1966332297","https://openalex.org/W2005694351","https://openalex.org/W2015780366","https://openalex.org/W2027000042","https://openalex.org/W2051446435","https://openalex.org/W2053772077","https://openalex.org/W2058840065","https://openalex.org/W2062520712","https://openalex.org/W2073989960","https://openalex.org/W2075712036","https://openalex.org/W2082699349","https://openalex.org/W2161381512","https://openalex.org/W2163311420","https://openalex.org/W2322727693","https://openalex.org/W2472563594","https://openalex.org/W2593771152","https://openalex.org/W2739310573","https://openalex.org/W2804248224","https://openalex.org/W2888107621","https://openalex.org/W2896070335","https://openalex.org/W2904704381","https://openalex.org/W2922102451","https://openalex.org/W2964335024","https://openalex.org/W2991855367","https://openalex.org/W2994072076","https://openalex.org/W3007391486","https://openalex.org/W3048826305","https://openalex.org/W4213266766","https://openalex.org/W4299647874"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3029198973","https://openalex.org/W2952813363","https://openalex.org/W4360783045","https://openalex.org/W2963346891","https://openalex.org/W3176438653"],"abstract_inverted_index":{"As":[0],"direct":[1],"response,":[2],"or":[3],"recovery":[4],"and":[5,18,72,146],"security":[6],"operations,":[7],"it":[8],"is":[9],"of":[10,22,37,44,65,74,82,96,109,126],"paramount":[11],"importance":[12],"to":[13,24,46,61,76],"establish":[14],"precisely":[15],"the":[16,20,42,48,51,70,80,124,144,150,169,174],"location":[17],"assess":[19],"extent":[21],"damage":[23,38,67,75,91,145],"a":[25,32,94,133,178],"building":[26,66],"as":[27,29,106],"quickly":[28],"possible":[30],"after":[31,149],"tragic":[33],"event.":[34],"The":[35,153,164],"automation":[36],"analysis":[39],"may":[40],"enhance":[41],"capability":[43],"administration":[45],"provide":[47],"help.":[49],"For":[50],"same,":[52],"convolutional":[53,102,114,135,161,171],"neural-networks":[54],"are":[55,117],"being":[56],"used":[57],"by":[58],"recent":[59,113,160],"proposals":[60],"perform":[62],"image":[63],"classification":[64],"depending":[68],"on":[69],"amount":[71],"type":[73],"be":[77],"detected.":[78],"Furthermore,":[79,112],"use":[81],"up/down-sampling":[83],"images":[84,108],"during":[85],"CNN":[86],"preparation":[87],"helps":[88],"in":[89,101,130],"better":[90],"recognition.":[92],"However,":[93],"number":[95],"challenges":[97],"has":[98,138,156],"been":[99,139,157],"observed":[100],"neural-networks-based":[103,115],"methods":[104],"such":[105],"multi-resolution":[107],"damaged":[110],"areas.":[111],"models":[116,176],"having":[118],"very":[119],"complex":[120],"architecture":[121],"which":[122,141],"increases":[123],"requirement":[125],"computational":[127],"power.":[128],"Therefore,":[129],"this":[131],"paper,":[132],"simple":[134,170],"neural-network":[136,162,172],"model":[137],"presented":[140,154],"effectively":[142],"identifies":[143],"undamaged":[147],"buildings":[148],"natural":[151],"disaster.":[152],"method":[155],"compared":[158],"with":[159,177],"models.":[163],"experimental":[165],"results":[166],"shows":[167],"that":[168],"outperforms":[173],"existing":[175],"99.2%":[179],"validation":[180],"accuracy.":[181]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}