{"id":"https://openalex.org/W4311081271","doi":"https://doi.org/10.1109/jstars.2022.3219724","title":"Comparative Study of Real-Time Semantic Segmentation Networks in Aerial Images During Flooding Events","display_name":"Comparative Study of Real-Time Semantic Segmentation Networks in Aerial Images During Flooding Events","publication_year":2022,"publication_date":"2022-11-04","ids":{"openalex":"https://openalex.org/W4311081271","doi":"https://doi.org/10.1109/jstars.2022.3219724"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2022.3219724","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2022.3219724","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/9973430/09939092.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/4609443/9973430/09939092.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023316624","display_name":"Farshad Safavi","orcid":"https://orcid.org/0000-0002-6905-0781"},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Farshad Safavi","raw_affiliation_strings":["Computer Science and Electrical Engineering, University of Maryland, Baltimore County, Baltimore, MD, USA"],"raw_orcid":"https://orcid.org/0000-0002-6905-0781","affiliations":[{"raw_affiliation_string":"Computer Science and Electrical Engineering, University of Maryland, Baltimore County, Baltimore, MD, USA","institution_ids":["https://openalex.org/I79272384"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010792548","display_name":"Maryam Rahnemoonfar","orcid":"https://orcid.org/0000-0001-9358-2836"},"institutions":[{"id":"https://openalex.org/I186143895","display_name":"Lehigh University","ror":"https://ror.org/012afjb06","country_code":"US","type":"education","lineage":["https://openalex.org/I186143895"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Maryam Rahnemoonfar","raw_affiliation_strings":["Departments of Computer Science and Engineering and Civil and Environmental Engineering, Lehigh University, Bethlehem, PA, USA"],"raw_orcid":"https://orcid.org/0000-0001-9358-2836","affiliations":[{"raw_affiliation_string":"Departments of Computer Science and Engineering and Civil and Environmental Engineering, Lehigh University, Bethlehem, PA, USA","institution_ids":["https://openalex.org/I186143895"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":{"value":1250,"currency":"USD","value_usd":1250},"fwci":2.832,"has_fulltext":true,"cited_by_count":39,"citation_normalized_percentile":{"value":0.92429845,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"16","issue":null,"first_page":"4","last_page":"20"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9993000030517578,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9993000030517578,"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"}},{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9908000230789185,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9896000027656555,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8184527158737183},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7518318295478821},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6506636738777161},{"id":"https://openalex.org/keywords/flooding","display_name":"Flooding (psychology)","score":0.6198250651359558},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6096880435943604},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5990451574325562},{"id":"https://openalex.org/keywords/aerial-image","display_name":"Aerial image","score":0.5846153497695923},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5007381439208984},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.49158915877342224},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4765637218952179},{"id":"https://openalex.org/keywords/aerial-imagery","display_name":"Aerial imagery","score":0.4254520535469055},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4150775969028473},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4026035964488983},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37040263414382935},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.34653764963150024},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.192718505859375},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.1465044617652893},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08861926198005676}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8184527158737183},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7518318295478821},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6506636738777161},{"id":"https://openalex.org/C186594467","wikidata":"https://www.wikidata.org/wiki/Q1429176","display_name":"Flooding (psychology)","level":2,"score":0.6198250651359558},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6096880435943604},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5990451574325562},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.5846153497695923},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5007381439208984},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.49158915877342224},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4765637218952179},{"id":"https://openalex.org/C2987819851","wikidata":"https://www.wikidata.org/wiki/Q191839","display_name":"Aerial imagery","level":2,"score":0.4254520535469055},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4150775969028473},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4026035964488983},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37040263414382935},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34653764963150024},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.192718505859375},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.1465044617652893},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08861926198005676},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/jstars.2022.3219724","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2022.3219724","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/9973430/09939092.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:6aa18bde807c4d848ad080e3e5acf920","is_oa":true,"landing_page_url":"https://doaj.org/article/6aa18bde807c4d848ad080e3e5acf920","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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 4-20 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/jstars.2022.3219724","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2022.3219724","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/9973430/09939092.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","score":0.6499999761581421,"display_name":"Climate action"}],"awards":[{"id":"https://openalex.org/G2802650612","display_name":null,"funder_award_id":"W911NF21-20076","funder_id":"https://openalex.org/F4320332447","funder_display_name":"U.S. Army"}],"funders":[{"id":"https://openalex.org/F4320307764","display_name":"Microsoft","ror":"https://ror.org/00d0nc645"},{"id":"https://openalex.org/F4320332447","display_name":"U.S. Army","ror":"https://ror.org/00afsp483"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4311081271.pdf","grobid_xml":"https://content.openalex.org/works/W4311081271.grobid-xml"},"referenced_works_count":118,"referenced_works":["https://openalex.org/W1535289548","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1905033729","https://openalex.org/W1912954554","https://openalex.org/W1969150627","https://openalex.org/W1988334140","https://openalex.org/W1996732587","https://openalex.org/W2000454085","https://openalex.org/W2066916495","https://openalex.org/W2087759065","https://openalex.org/W2098676252","https://openalex.org/W2099688631","https://openalex.org/W2108598243","https://openalex.org/W2125637308","https://openalex.org/W2169551590","https://openalex.org/W2194775991","https://openalex.org/W2279098554","https://openalex.org/W2324379549","https://openalex.org/W2340897893","https://openalex.org/W2412588858","https://openalex.org/W2412782625","https://openalex.org/W2476169391","https://openalex.org/W2507296351","https://openalex.org/W2531409750","https://openalex.org/W2560023338","https://openalex.org/W2620630829","https://openalex.org/W2630837129","https://openalex.org/W2739310573","https://openalex.org/W2751694392","https://openalex.org/W2767943769","https://openalex.org/W2774320778","https://openalex.org/W2778764040","https://openalex.org/W2782861076","https://openalex.org/W2786492053","https://openalex.org/W2794948653","https://openalex.org/W2798122215","https://openalex.org/W2799213142","https://openalex.org/W2884436604","https://openalex.org/W2886934227","https://openalex.org/W2896365540","https://openalex.org/W2898504016","https://openalex.org/W2902190145","https://openalex.org/W2904704381","https://openalex.org/W2912989244","https://openalex.org/W2924082650","https://openalex.org/W2960964942","https://openalex.org/W2962850830","https://openalex.org/W2963125010","https://openalex.org/W2963446712","https://openalex.org/W2963881378","https://openalex.org/W2964217532","https://openalex.org/W2971198903","https://openalex.org/W2979717888","https://openalex.org/W2982083293","https://openalex.org/W2982106100","https://openalex.org/W2982182858","https://openalex.org/W2987039128","https://openalex.org/W2987175876","https://openalex.org/W2990138404","https://openalex.org/W2990500698","https://openalex.org/W2995808743","https://openalex.org/W2995856394","https://openalex.org/W3007268491","https://openalex.org/W3014641072","https://openalex.org/W3017361373","https://openalex.org/W3021621446","https://openalex.org/W3027542479","https://openalex.org/W3032433182","https://openalex.org/W3034238686","https://openalex.org/W3034785488","https://openalex.org/W3035600434","https://openalex.org/W3045188463","https://openalex.org/W3049146357","https://openalex.org/W3091812030","https://openalex.org/W3104341624","https://openalex.org/W3107725261","https://openalex.org/W3110908156","https://openalex.org/W3118458748","https://openalex.org/W3120898603","https://openalex.org/W3122445164","https://openalex.org/W3127751679","https://openalex.org/W3129110783","https://openalex.org/W3137356689","https://openalex.org/W3162524694","https://openalex.org/W3164538928","https://openalex.org/W3175205795","https://openalex.org/W3175373394","https://openalex.org/W3177272171","https://openalex.org/W3190860548","https://openalex.org/W3196904463","https://openalex.org/W3206475182","https://openalex.org/W3206476077","https://openalex.org/W3211490618","https://openalex.org/W4200321698","https://openalex.org/W4205569865","https://openalex.org/W4205806420","https://openalex.org/W4225016626","https://openalex.org/W4226244266","https://openalex.org/W4283450732","https://openalex.org/W4293406525","https://openalex.org/W4297775537","https://openalex.org/W4386076267","https://openalex.org/W6695314431","https://openalex.org/W6717372056","https://openalex.org/W6737664043","https://openalex.org/W6739696289","https://openalex.org/W6748692255","https://openalex.org/W6750469568","https://openalex.org/W6757225884","https://openalex.org/W6762718338","https://openalex.org/W6776411772","https://openalex.org/W6776821665","https://openalex.org/W6785680793","https://openalex.org/W6789654255","https://openalex.org/W6790275670","https://openalex.org/W6797399245","https://openalex.org/W6799579066"],"related_works":["https://openalex.org/W4283696875","https://openalex.org/W3110585990","https://openalex.org/W4385767632","https://openalex.org/W2898690910","https://openalex.org/W2784132289","https://openalex.org/W4286697184","https://openalex.org/W2889700547","https://openalex.org/W2889866244","https://openalex.org/W3034139063","https://openalex.org/W2593313455"],"abstract_inverted_index":{"Real-time":[0],"semantic":[1,24,88],"segmentation":[2,25,89,178],"of":[3,68,129,140,176],"aerial":[4,59,97,119,147,181],"imagery":[5,120],"is":[6],"essential":[7],"for":[8,35,58,146,180],"unmanned":[9],"ariel":[10],"vehicle":[11],"applications,":[12],"including":[13,110],"military":[14],"surveillance,":[15],"land":[16],"characterization,":[17],"and":[18,31,55,112,127,163,174,186],"disaster":[19],"damage":[20],"assessments.":[21],"Recent":[22],"real-time":[23,87],"neural":[26],"networks":[27],"promise":[28],"low":[29,184],"computation":[30,185],"inference":[32,187],"time,":[33],"appropriate":[34],"resource-limited":[36],"platforms,":[37],"such":[38,52,74,197],"as":[39,53,75,198],"edge":[40],"devices.":[41],"However,":[42],"these":[43,69,80,141],"methods":[44],"are":[45],"mainly":[46],"trained":[47],"on":[48,91,118,132,159,167],"human-centric":[49],"view":[50],"datasets,":[51],"Cityscapes":[54],"CamVid,":[56],"unsuitable":[57],"applications.":[60],"Furthermore,":[61],"we":[62,82,123],"do":[63],"not":[64],"know":[65],"the":[66,84,92,125,133,138,160,172],"feasibility":[67],"models":[70,131,142,152,179],"under":[71],"adversarial":[72],"settings,":[73],"flooding":[76,199],"events.":[77,200],"To":[78],"solve":[79],"problems,":[81],"train":[83],"most":[85],"recent":[86],"architectures":[90],"FloodNet":[93,134,161],"dataset":[94,135,162],"containing":[95],"annotated":[96],"images":[98],"captured":[99],"after":[100],"hurricane":[101],"Harvey.":[102],"This":[103,169],"article":[104,170],"comprehensively":[105],"studies":[106],"several":[107],"lightweight":[108,151],"architectures,":[109,114],"encoder\u2013decoder":[111],"two-pathway":[113],"evaluating":[115],"their":[116],"performance":[117],"datasets.":[121],"Moreover,":[122],"benchmark":[124],"efficiency":[126],"accuracy":[128],"different":[130],"to":[136],"examine":[137],"practicability":[139],"during":[143,194],"emergency":[144],"response":[145],"image":[148],"segmentation.":[149],"Some":[150],"attain":[153],"more":[154],"than":[155],"60%":[156],"test":[157],"mIoU":[158],"yield":[164],"qualitative":[165],"results":[166],"images.":[168],"highlights":[171],"strengths":[173],"weaknesses":[175],"current":[177],"imagery,":[182],"requiring":[183],"time.":[188],"Our":[189],"experiment":[190],"has":[191],"direct":[192],"applications":[193],"catastrophic":[195],"events,":[196]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":8}],"updated_date":"2026-08-14T07:06:38.338062","created_date":"2025-10-10T00:00:00"}