{"id":"https://openalex.org/W4387272150","doi":"https://doi.org/10.1109/access.2023.3321312","title":"DX-FloodLine: End-To-End Deep Explainable Pipeline for Real Time Flood Scene Object Detection From Multimedia Images","display_name":"DX-FloodLine: End-To-End Deep Explainable Pipeline for Real Time Flood Scene Object Detection From Multimedia Images","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4387272150","doi":"https://doi.org/10.1109/access.2023.3321312"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3321312","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3321312","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10268967.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10268967.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063382634","display_name":"Nushrat Humaira","orcid":"https://orcid.org/0000-0002-6602-6305"},"institutions":[{"id":"https://openalex.org/I8078737","display_name":"Clemson University","ror":"https://ror.org/037s24f05","country_code":"US","type":"education","lineage":["https://openalex.org/I8078737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nushrat Humaira","raw_affiliation_strings":["School of Computing, Clemson University, Clemson, SC, USA"],"raw_orcid":"https://orcid.org/0000-0002-6602-6305","affiliations":[{"raw_affiliation_string":"School of Computing, Clemson University, Clemson, SC, USA","institution_ids":["https://openalex.org/I8078737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110761875","display_name":"Vidya Samadi","orcid":null},"institutions":[{"id":"https://openalex.org/I8078737","display_name":"Clemson University","ror":"https://ror.org/037s24f05","country_code":"US","type":"education","lineage":["https://openalex.org/I8078737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vidya S. Samadi","raw_affiliation_strings":["Department of Agricultural Sciences, Clemson University, Clemson, SC, USA"],"raw_orcid":"https://orcid.org/0000-0003-1494-6481","affiliations":[{"raw_affiliation_string":"Department of Agricultural Sciences, Clemson University, Clemson, SC, USA","institution_ids":["https://openalex.org/I8078737"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071884087","display_name":"Nina Hubig","orcid":"https://orcid.org/0000-0002-8911-7832"},"institutions":[{"id":"https://openalex.org/I8078737","display_name":"Clemson University","ror":"https://ror.org/037s24f05","country_code":"US","type":"education","lineage":["https://openalex.org/I8078737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nina C. Hubig","raw_affiliation_strings":["School of Computing, Clemson University, Charleston, SC, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing, Clemson University, Charleston, SC, USA","institution_ids":["https://openalex.org/I8078737"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I8078737"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.5241,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.81618342,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"11","issue":null,"first_page":"110644","last_page":"110655"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10930","display_name":"Flood Risk Assessment and Management","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10930","display_name":"Flood Risk Assessment and Management","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9869999885559082,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11483","display_name":"Tropical and Extratropical Cyclones Research","score":0.9832000136375427,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.805933952331543},{"id":"https://openalex.org/keywords/flood-myth","display_name":"Flood myth","score":0.6757653951644897},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.5915734767913818},{"id":"https://openalex.org/keywords/flooding","display_name":"Flooding (psychology)","score":0.5723997354507446},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5520246624946594},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.532621443271637},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.47512751817703247},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.47112059593200684},{"id":"https://openalex.org/keywords/flash-flood","display_name":"Flash flood","score":0.4314955174922943},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3848017454147339},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3585164546966553},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32421955466270447},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.23126038908958435},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.1733429729938507},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.13479915261268616}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.805933952331543},{"id":"https://openalex.org/C74256435","wikidata":"https://www.wikidata.org/wiki/Q134052","display_name":"Flood myth","level":2,"score":0.6757653951644897},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.5915734767913818},{"id":"https://openalex.org/C186594467","wikidata":"https://www.wikidata.org/wiki/Q1429176","display_name":"Flooding (psychology)","level":2,"score":0.5723997354507446},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5520246624946594},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.532621443271637},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.47512751817703247},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.47112059593200684},{"id":"https://openalex.org/C120417685","wikidata":"https://www.wikidata.org/wiki/Q860333","display_name":"Flash flood","level":3,"score":0.4314955174922943},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3848017454147339},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3585164546966553},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32421955466270447},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.23126038908958435},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.1733429729938507},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.13479915261268616},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2023.3321312","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3321312","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10268967.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:d59612ab00614f02bfd0a5c7105421df","is_oa":true,"landing_page_url":"https://doaj.org/article/d59612ab00614f02bfd0a5c7105421df","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 11, Pp 110644-110655 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3321312","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3321312","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10268967.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","score":0.4300000071525574,"display_name":"Climate action"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320309106","display_name":"Clemson University","ror":"https://ror.org/037s24f05"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4387272150.pdf","grobid_xml":"https://content.openalex.org/works/W4387272150.grobid-xml"},"referenced_works_count":54,"referenced_works":["https://openalex.org/W582134693","https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W1686810756","https://openalex.org/W1861492603","https://openalex.org/W1866206747","https://openalex.org/W2101926813","https://openalex.org/W2112796928","https://openalex.org/W2117539524","https://openalex.org/W2118858186","https://openalex.org/W2330219538","https://openalex.org/W2534171296","https://openalex.org/W2594633041","https://openalex.org/W2605409611","https://openalex.org/W2618530766","https://openalex.org/W2739195437","https://openalex.org/W2798717693","https://openalex.org/W2902840110","https://openalex.org/W2912334076","https://openalex.org/W2941434910","https://openalex.org/W2962962930","https://openalex.org/W2963037989","https://openalex.org/W2963150697","https://openalex.org/W2963167203","https://openalex.org/W2963611739","https://openalex.org/W2968453622","https://openalex.org/W2970003526","https://openalex.org/W3007088614","https://openalex.org/W3012120038","https://openalex.org/W3013282987","https://openalex.org/W3014247716","https://openalex.org/W3033210410","https://openalex.org/W3033674996","https://openalex.org/W3036529666","https://openalex.org/W3045953689","https://openalex.org/W3080501295","https://openalex.org/W3085380432","https://openalex.org/W3118608800","https://openalex.org/W4200321698","https://openalex.org/W4206730114","https://openalex.org/W4316116082","https://openalex.org/W4385245566","https://openalex.org/W6617145748","https://openalex.org/W6637373629","https://openalex.org/W6639102338","https://openalex.org/W6639216784","https://openalex.org/W6677919164","https://openalex.org/W6734194636","https://openalex.org/W6736518430","https://openalex.org/W6739901393","https://openalex.org/W6766990963","https://openalex.org/W6775115414","https://openalex.org/W6779248606","https://openalex.org/W6783213970"],"related_works":["https://openalex.org/W2906253252","https://openalex.org/W4243891849","https://openalex.org/W3044343163","https://openalex.org/W3040763774","https://openalex.org/W2148193050","https://openalex.org/W2181997527","https://openalex.org/W4286560687","https://openalex.org/W2943433098","https://openalex.org/W2031888665","https://openalex.org/W2923835640"],"abstract_inverted_index":{"In":[0,86],"recent":[1],"years,":[2],"an":[3,29,105],"alarming":[4],"number":[5],"of":[6,166],"natural":[7],"disasters,":[8],"specifically":[9],"hurricanes":[10],"and":[11,37,44,52,74,124,128,190,200,204,225],"floods":[12],"have":[13,28,60],"affected":[14],"the":[15,163],"United":[16],"States.":[17],"Flooding":[18],"is":[19,47,67],"a":[20,135,143,230],"global":[21],"crisis,":[22],"however":[23],"we":[24],"still":[25],"do":[26],"not":[27],"automated":[30],"approach":[31],"for":[32,49,79,100,140,176,194],"real-time":[33],"flood":[34,80,120,141,159,184,209,213],"risk":[35],"detection":[36],"mitigation.":[38],"Detecting":[39],"inundation":[40],"in":[41,63,82,160,162],"urban":[42],"areas":[43],"road":[45],"segments":[46],"crucial":[48],"vehicle":[50],"routing":[51],"traffic":[53],"management.":[54],"Unlike":[55],"remote":[56],"sensing":[57],"images":[58,76,123,161],"that":[59],"been":[61],"used":[62],"past":[64],"studies,":[65],"it":[66],"better":[68],"to":[69,114,168,173,183,186],"mine":[70],"social":[71,94],"media":[72,95],"data":[73],"geo-tagged":[75],"or":[77],"videos":[78],"estimation":[81],"near":[83,116,205],"real":[84,117,206],"time.":[85],"this":[87],"paper,":[88],"multimedia":[89],"content":[90],"was":[91,198],"collected":[92],"from":[93,122],"streaming":[96],"services,":[97],"primarily":[98],"Twitter":[99],"analysis.":[101],"We":[102,133,179],"propose":[103],"DX-FloodLine,":[104],"interpretable,":[106],"intelligent,":[107],"multi-stage,":[108],"end-to-end,":[109],"deep":[110],"neural":[111,138],"network-based":[112],"pipeline":[113],"classify":[115],"time":[118,207],"emerging":[119],"occurrence":[121],"detect":[125],"submerged":[126],"objects":[127],"pedestrians":[129],"around":[130,217],"flooded":[131],"regions.":[132],"introduce":[134],"novel":[136,155],"hybrid":[137],"network":[139],"detection,":[142],"VGG16(Visual":[144],"Geometry":[145],"Group":[146],"16-layer":[147],"model)-LSTM":[148],"(Long":[149],"short":[150],"term":[151],"memory)":[152],"ensemble.":[153],"Our":[154,211],"ensemble":[156],"architecture":[157],"recognizes":[158],"first":[164],"stage":[165,175],"pipeline,":[167],"be":[169],"later":[170],"passed":[171],"on":[172,202,221],"second":[174],"object":[177],"detection.":[178],"applied":[180],"interpretable":[181],"models":[182],"classifiers":[185],"identify":[187],"model":[188,215],"shortcomings":[189],"then":[191],"incrementally":[192],"train":[193],"continuous":[195],"improvement.":[196],"DX-FloodLine":[197],"deployed":[199],"tested":[201],"unseen":[203],"streamed":[208],"images.":[210],"VGG16-LSTM":[212],"recognition":[214],"achieved":[216],"90%":[218],"validation":[219],"accuracy":[220],"multiple":[222],"benchmark":[223],"studies":[224],"surpassed":[226],"other":[227],"competitors":[228],"by":[229],"good":[231],"margin.":[232]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
