{"id":"https://openalex.org/W4386608076","doi":"https://doi.org/10.3390/s23187766","title":"Anthropogenic Object Localization: Evaluation of Broad-Area High-Resolution Imagery Scans Using Deep Learning in Overhead Imagery","display_name":"Anthropogenic Object Localization: Evaluation of Broad-Area High-Resolution Imagery Scans Using Deep Learning in Overhead Imagery","publication_year":2023,"publication_date":"2023-09-08","ids":{"openalex":"https://openalex.org/W4386608076","doi":"https://doi.org/10.3390/s23187766","pmid":"https://pubmed.ncbi.nlm.nih.gov/37765824"},"language":"en","primary_location":{"id":"doi:10.3390/s23187766","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23187766","pdf_url":"https://www.mdpi.com/1424-8220/23/18/7766/pdf?version=1694309835","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/23/18/7766/pdf?version=1694309835","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5009311723","display_name":"J. Alex Hurt","orcid":"https://orcid.org/0000-0002-7234-1301"},"institutions":[{"id":"https://openalex.org/I76835614","display_name":"University of Missouri","ror":"https://ror.org/02ymw8z06","country_code":"US","type":"education","lineage":["https://openalex.org/I76835614"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"J. Alex Hurt","raw_affiliation_strings":["Center for Geospatial Intelligence, University of Missouri, Columbia, MO 65211, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Geospatial Intelligence, University of Missouri, Columbia, MO 65211, USA","institution_ids":["https://openalex.org/I76835614"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044728758","display_name":"Ilinca Popescu","orcid":null},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ilinca Popescu","raw_affiliation_strings":["Department of Geography, Stanford University, Stanford, CA 94305, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Geography, Stanford University, Stanford, CA 94305, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079391589","display_name":"Curt H. Davis","orcid":"https://orcid.org/0000-0002-5781-0931"},"institutions":[{"id":"https://openalex.org/I76835614","display_name":"University of Missouri","ror":"https://ror.org/02ymw8z06","country_code":"US","type":"education","lineage":["https://openalex.org/I76835614"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Curt H. Davis","raw_affiliation_strings":["Center for Geospatial Intelligence, University of Missouri, Columbia, MO 65211, USA","Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65211, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Geospatial Intelligence, University of Missouri, Columbia, MO 65211, USA","institution_ids":["https://openalex.org/I76835614"]},{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65211, USA","institution_ids":["https://openalex.org/I76835614"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051712346","display_name":"Grant J. Scott","orcid":"https://orcid.org/0000-0001-5870-9387"},"institutions":[{"id":"https://openalex.org/I76835614","display_name":"University of Missouri","ror":"https://ror.org/02ymw8z06","country_code":"US","type":"education","lineage":["https://openalex.org/I76835614"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Grant J. Scott","raw_affiliation_strings":["Center for Geospatial Intelligence, University of Missouri, Columbia, MO 65211, USA","Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65211, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Geospatial Intelligence, University of Missouri, Columbia, MO 65211, USA","institution_ids":["https://openalex.org/I76835614"]},{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65211, USA","institution_ids":["https://openalex.org/I76835614"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5009311723"],"corresponding_institution_ids":["https://openalex.org/I76835614"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2673},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2673},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13220514,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"23","issue":"18","first_page":"7766","last_page":"7766"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9997000098228455,"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":0.9997000098228455,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9991000294685364,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9973999857902527,"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/remote-sensing","display_name":"Remote sensing","score":0.6773439645767212},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.545071005821228},{"id":"https://openalex.org/keywords/satellite-imagery","display_name":"Satellite imagery","score":0.5121631622314453},{"id":"https://openalex.org/keywords/high-resolution","display_name":"High resolution","score":0.5101292729377747},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4981989860534668},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.49533119797706604},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.48418357968330383},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.475167453289032},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.43930521607398987},{"id":"https://openalex.org/keywords/aerial-imagery","display_name":"Aerial imagery","score":0.43202877044677734},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.32809263467788696}],"concepts":[{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6773439645767212},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.545071005821228},{"id":"https://openalex.org/C2778102629","wikidata":"https://www.wikidata.org/wiki/Q725252","display_name":"Satellite imagery","level":2,"score":0.5121631622314453},{"id":"https://openalex.org/C3020199158","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"High resolution","level":2,"score":0.5101292729377747},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4981989860534668},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49533119797706604},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.48418357968330383},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.475167453289032},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.43930521607398987},{"id":"https://openalex.org/C2987819851","wikidata":"https://www.wikidata.org/wiki/Q191839","display_name":"Aerial imagery","level":2,"score":0.43202877044677734},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.32809263467788696},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/s23187766","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23187766","pdf_url":"https://www.mdpi.com/1424-8220/23/18/7766/pdf?version=1694309835","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:37765824","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37765824","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:10537164","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10537164","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10537164/pdf/sensors-23-07766.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:e98648adeed643399978b3ddf0007475","is_oa":true,"landing_page_url":"https://doaj.org/article/e98648adeed643399978b3ddf0007475","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":"Sensors, Vol 23, Iss 18, p 7766 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/23/18/7766/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s23187766","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s23187766","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23187766","pdf_url":"https://www.mdpi.com/1424-8220/23/18/7766/pdf?version=1694309835","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.49000000953674316}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4386608076.pdf"},"referenced_works_count":33,"referenced_works":["https://openalex.org/W946771493","https://openalex.org/W1576332977","https://openalex.org/W1980038761","https://openalex.org/W2001123951","https://openalex.org/W2015386604","https://openalex.org/W2020912318","https://openalex.org/W2120494907","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2588561483","https://openalex.org/W2592962403","https://openalex.org/W2626107033","https://openalex.org/W2763968347","https://openalex.org/W2808436940","https://openalex.org/W2919352650","https://openalex.org/W2943949784","https://openalex.org/W2946948417","https://openalex.org/W2963131120","https://openalex.org/W2964081807","https://openalex.org/W2992027343","https://openalex.org/W2996836954","https://openalex.org/W3011156941","https://openalex.org/W3012326541","https://openalex.org/W3121566766","https://openalex.org/W3128592650","https://openalex.org/W3137907778","https://openalex.org/W3151168706","https://openalex.org/W3167431782","https://openalex.org/W4248710273","https://openalex.org/W4383376375","https://openalex.org/W4385226200","https://openalex.org/W6638806006","https://openalex.org/W6793591400"],"related_works":["https://openalex.org/W3175687857","https://openalex.org/W3035955015","https://openalex.org/W829838075","https://openalex.org/W3205065304","https://openalex.org/W2903740016","https://openalex.org/W2280104667","https://openalex.org/W3200264477","https://openalex.org/W2894790411","https://openalex.org/W3033117077","https://openalex.org/W150600545"],"abstract_inverted_index":{"Too":[0],"often,":[1],"the":[2,12,28,34,68,72,81,87,91,119,123,188,209,212,220,228,234,251,264],"testing":[3],"and":[4,85,122,140,144,149,178,232,254],"evaluation":[5,73,210],"of":[6,39,63,67,74,80,93,109,111,127,132,187,211,214,222,227,256,261,267],"object":[7,167,200,273],"detection,":[8,253],"as":[9,11,173,203,205],"well":[10,204],"classification":[13],"techniques":[14,182],"for":[15,137,155,198,208,250,271],"high-resolution":[16],"remote":[17,52],"sensing":[18,53],"imagery,":[19,262],"are":[20,55],"confined":[21],"to":[22,99,118,147,183,243],"clean,":[23],"discretely":[24],"partitioned":[25],"datasets,":[26],"i.e.,":[27],"closed-world":[29],"model.":[30],"In":[31,158],"recent":[32],"years,":[33],"performance":[35],"on":[36,103],"a":[37,104,206,240,269],"number":[38],"benchmark":[40,170],"datasets":[41,171],"has":[42],"exceeded":[43],"99%":[44],"when":[45],"evaluated":[46],"using":[47,166],"cross-validation":[48],"techniques.":[49],"However,":[50],"real-world":[51,156,235,279],"data":[54],"truly":[56],"big":[57],"data,":[58],"which":[59],"often":[60],"exceed":[61],"billions":[62],"pixels.":[64],"Therefore,":[65],"one":[66],"greatest":[69],"challenges":[70,221],"regarding":[71],"machine":[75,275],"learning":[76,276],"models":[77,102,162,225,277],"taken":[78],"out":[79,226],"clean":[82],"laboratory":[83,230],"setting":[84,231],"into":[86,233],"real":[88],"world":[89],"is":[90,97,116,146],"difficulty":[92],"measuring":[94],"performance.":[95],"It":[96],"necessary":[98],"evaluate":[100],"these":[101,224],"grander":[105],"scale,":[106],"namely,":[107],"tens":[108],"thousands":[110],"square":[112],"kilometers,":[113],"where":[114],"it":[115],"intractable":[117],"ground":[120],"truth":[121],"ever-changing":[124],"anthropogenic":[125],"surface":[126],"Earth.":[128],"The":[129],"ultimate":[130,265],"goal":[131,266],"computer":[133],"vision":[134],"model":[135],"development":[136],"automated":[138],"analysis":[139],"broad":[141,185],"area":[142],"search":[143],"discovery":[145],"augment":[148],"assist":[150],"humans,":[151],"specifically":[152],"human-machine":[153],"teaming":[154],"tasks.":[157],"this":[159],"research,":[160],"various":[161],"have":[163],"been":[164],"trained":[165],"classes":[168],"from":[169],"such":[172],"UC":[174],"Merced,":[175],"PatternNet,":[176],"RESISC-45,":[177],"MDSv2.":[179],"We":[180,195,238],"detail":[181],"scan":[184],"swaths":[186,260],"Earth":[189],"with":[190,263],"deep":[191,246],"convolutional":[192,247],"neural":[193,248],"networks.":[194],"present":[196],"algorithms":[197],"localizing":[199],"detection":[201,274],"results,":[202],"methodology":[207,270],"results":[213],"broad-area":[215],"scans.":[216],"Our":[217],"research":[218],"explores":[219],"transitioning":[223],"training-validation":[229],"application":[236],"domain.":[237],"show":[239],"scalable":[241],"approach":[242],"leverage":[244],"state-of-the-art":[245],"networks":[249],"search,":[252],"annotation":[255],"objects":[257],"within":[258],"large":[259],"providing":[268],"evaluating":[272],"in":[278],"scenarios.":[280]},"counts_by_year":[],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
