{"id":"https://openalex.org/W2731489139","doi":"https://doi.org/10.3390/rs9070701","title":"Optimal Seamline Detection for Orthoimage Mosaicking by Combining Deep Convolutional Neural Network and Graph Cuts","display_name":"Optimal Seamline Detection for Orthoimage Mosaicking by Combining Deep Convolutional Neural Network and Graph Cuts","publication_year":2017,"publication_date":"2017-07-07","ids":{"openalex":"https://openalex.org/W2731489139","doi":"https://doi.org/10.3390/rs9070701","mag":"2731489139"},"language":"en","primary_location":{"id":"doi:10.3390/rs9070701","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs9070701","pdf_url":"https://www.mdpi.com/2072-4292/9/7/701/pdf?version=1499440215","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"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":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/9/7/701/pdf?version=1499440215","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100361330","display_name":"Li Li","orcid":"https://orcid.org/0000-0003-1381-0654"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Li","raw_affiliation_strings":["School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, Hubei, China"],"affiliations":[{"raw_affiliation_string":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, Hubei, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011274467","display_name":"Jian Yao","orcid":"https://orcid.org/0000-0002-9134-5084"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jian Yao","raw_affiliation_strings":["School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, Hubei, China"],"affiliations":[{"raw_affiliation_string":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, Hubei, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100375513","display_name":"Yahui Liu","orcid":"https://orcid.org/0000-0003-4398-8867"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yahui Liu","raw_affiliation_strings":["School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, Hubei, China"],"affiliations":[{"raw_affiliation_string":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, Hubei, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034840625","display_name":"Wei Yuan","orcid":"https://orcid.org/0000-0002-1370-0079"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["CN","JP"],"is_corresponding":false,"raw_author_name":"Wei Yuan","raw_affiliation_strings":["Center for Spatial Information Science, University of Tokyo, Kashiwa 277-8568, Japan","School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, Hubei, China"],"affiliations":[{"raw_affiliation_string":"Center for Spatial Information Science, University of Tokyo, Kashiwa 277-8568, Japan","institution_ids":["https://openalex.org/I74801974"]},{"raw_affiliation_string":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, Hubei, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056109786","display_name":"Shuzhu Shi","orcid":"https://orcid.org/0000-0003-0228-402X"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuzhu Shi","raw_affiliation_strings":["School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, Hubei, China"],"affiliations":[{"raw_affiliation_string":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, Hubei, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033906757","display_name":"Shenggu Yuan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shenggu Yuan","raw_affiliation_strings":["China Transport Telecommunications and Information Center, Beijing 100011, China"],"affiliations":[{"raw_affiliation_string":"China Transport Telecommunications and Information Center, Beijing 100011, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5011274467"],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":3.7809,"has_fulltext":true,"cited_by_count":33,"citation_normalized_percentile":{"value":0.92522353,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"9","issue":"7","first_page":"701","last_page":"701"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"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/T13282","display_name":"Automated Road and Building Extraction","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9987999796867371,"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":0.7875704765319824},{"id":"https://openalex.org/keywords/orthophoto","display_name":"Orthophoto","score":0.7203951478004456},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7113776206970215},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6553271412849426},{"id":"https://openalex.org/keywords/cut","display_name":"Cut","score":0.6336409449577332},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5605456233024597},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5576446056365967},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4949023127555847},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.48331499099731445},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.48011279106140137},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4414343237876892},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.43189069628715515},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.41038379073143005}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7875704765319824},{"id":"https://openalex.org/C82789328","wikidata":"https://www.wikidata.org/wiki/Q922585","display_name":"Orthophoto","level":2,"score":0.7203951478004456},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7113776206970215},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6553271412849426},{"id":"https://openalex.org/C5134670","wikidata":"https://www.wikidata.org/wiki/Q1626444","display_name":"Cut","level":4,"score":0.6336409449577332},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5605456233024597},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5576446056365967},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4949023127555847},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.48331499099731445},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.48011279106140137},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4414343237876892},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.43189069628715515},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.41038379073143005},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","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/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs9070701","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs9070701","pdf_url":"https://www.mdpi.com/2072-4292/9/7/701/pdf?version=1499440215","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"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":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:5b4deffb7ef1493aa06e4e2f10c293b9","is_oa":true,"landing_page_url":"https://doaj.org/article/5b4deffb7ef1493aa06e4e2f10c293b9","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 9, Iss 7, p 701 (2017)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/9/7/701/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs9070701","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":"Remote Sensing","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs9070701","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs9070701","pdf_url":"https://www.mdpi.com/2072-4292/9/7/701/pdf?version=1499440215","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"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":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.6600000262260437,"display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1469578410","display_name":null,"funder_award_id":"No. 41571436","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2178369055","display_name":null,"funder_award_id":"41571436","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G37568934","display_name":null,"funder_award_id":"Grant","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G391238517","display_name":null,"funder_award_id":", and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4020255992","display_name":null,"funder_award_id":"Project","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5074176246","display_name":null,"funder_award_id":"Project No. 41571436","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5219481562","display_name":null,"funder_award_id":"91438203","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5939423041","display_name":null,"funder_award_id":"Technology","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6809183074","display_name":null,"funder_award_id":"Project No.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320326938","display_name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing","ror":"https://ror.org/02bpap860"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2731489139.pdf","grobid_xml":"https://content.openalex.org/works/W2731489139.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W114517082","https://openalex.org/W1665214252","https://openalex.org/W1903029394","https://openalex.org/W1905829557","https://openalex.org/W1968979303","https://openalex.org/W1982254880","https://openalex.org/W1986557861","https://openalex.org/W2001933992","https://openalex.org/W2007572995","https://openalex.org/W2018680401","https://openalex.org/W2021193738","https://openalex.org/W2025218989","https://openalex.org/W2027302630","https://openalex.org/W2035206677","https://openalex.org/W2048292156","https://openalex.org/W2064972255","https://openalex.org/W2072176627","https://openalex.org/W2104095591","https://openalex.org/W2105949881","https://openalex.org/W2113137767","https://openalex.org/W2118080570","https://openalex.org/W2125267934","https://openalex.org/W2133665775","https://openalex.org/W2136208183","https://openalex.org/W2137940195","https://openalex.org/W2143516773","https://openalex.org/W2155893237","https://openalex.org/W2157189144","https://openalex.org/W2169528473","https://openalex.org/W2215966420","https://openalex.org/W2222612055","https://openalex.org/W2243233073","https://openalex.org/W2286878445","https://openalex.org/W2567356819","https://openalex.org/W4236692733"],"related_works":["https://openalex.org/W2375137989","https://openalex.org/W2906447781","https://openalex.org/W4244208072","https://openalex.org/W2010171670","https://openalex.org/W2109407305","https://openalex.org/W2032319136","https://openalex.org/W2897997384","https://openalex.org/W2088651901","https://openalex.org/W1544828638","https://openalex.org/W2086619084"],"abstract_inverted_index":{"When":[0],"mosaicking":[1,50],"orthoimages,":[2,267],"especially":[3],"in":[4,69,77,104,118],"urban":[5,264],"areas":[6],"with":[7,51],"various":[8],"obvious":[9],"ground":[10],"objects":[11],"like":[12],"buildings,":[13],"roads,":[14],"cars":[15],"or":[16,197],"trees,":[17],"the":[18,26,52,86,112,119,126,134,139,145,153,168,179,183,191,211,219,232,239,243,254,270,274,279,289],"detection":[19],"of":[20,25,54,72,85,115,129,133,149,162,182,189,194,205,221,249,259],"optimal":[21,46,140,222],"seamlines":[22,47,141,262],"is":[23,83,122,166,209,226,257],"one":[24,84],"key":[27],"technologies":[28],"for":[29,48,99],"creating":[30],"seamless":[31],"and":[32,60,75,80,265,268,273,284],"pleasant":[33],"image":[34,192,240],"mosaics.":[35],"In":[36],"this":[37],"paper,":[38],"we":[39,143],"propose":[40,95],"a":[41,96],"new":[42],"approach":[43],"to":[44,131,217,237],"detect":[45],"orthoimage":[49],"use":[53],"deep":[55,97],"convolutional":[56],"neural":[57],"network":[58],"(CNN)":[59],"graph":[61,81,154],"cuts.":[62],"Deep":[63],"CNNs":[64],"have":[65],"been":[66],"widely":[67,88],"used":[68,89,216],"many":[70],"fields":[71],"computer":[73],"vision":[74],"photogrammetry":[76],"recent":[78],"years,":[79],"cuts":[82,155],"most":[87],"energy":[90,113,147,156,171],"optimization":[91],"frameworks.":[92],"We":[93],"first":[94],"CNN":[98,184],"land":[100],"cover":[101],"semantic":[102,186,212],"segmentation":[103,187],"overlap":[105,120],"regions":[106,121],"between":[107,173],"two":[108,174],"adjacent":[109],"images.":[110],"Then,":[111],"cost":[114],"each":[116,132],"pixel":[117,169],"defined":[123,177,236],"based":[124,185,277,287],"on":[125,246,278,288],"classification":[127,180],"probabilities":[128],"belonging":[130],"specified":[135],"classes.":[136],"To":[137],"find":[138],"globally,":[142],"fuse":[144],"CNN-classified":[146],"costs":[148,172],"all":[150],"pixels":[151],"into":[152],"minimization":[157],"framework.":[158],"The":[159],"main":[160],"advantage":[161,204],"our":[163,206],"proposed":[164,207,255],"method":[165,208,256],"that":[167,210,253],"similarity":[170,291],"images":[175],"are":[176,214],"using":[178,190,231],"results":[181,245],"instead":[188],"informations":[193,213],"color,":[195],"gradient":[196],"texture":[198],"as":[199],"traditional":[200],"methods":[201],"do.":[202],"Another":[203],"fully":[215],"guide":[218],"process":[220],"seamline":[223],"detection,":[224],"which":[225],"more":[227],"reasonable":[228],"than":[229],"only":[230],"hand":[233],"designed":[234],"features":[235],"represent":[238],"differences.":[241],"Finally,":[242],"experimental":[244],"several":[247],"groups":[248],"challenging":[250],"orthoimages":[251],"show":[252],"capable":[258],"finding":[260],"high-quality":[261],"among":[263],"non-urban":[266],"outperforms":[269],"state-of-the-art":[271],"algorithms":[272],"commercial":[275],"software":[276],"visual":[280],"comparison,":[281],"statistical":[282],"evaluation":[283,286],"quantitative":[285],"structural":[290],"(SSIM)":[292],"index.":[293]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":7},{"year":2017,"cited_by_count":1}],"updated_date":"2026-04-18T07:56:08.524223","created_date":"2025-10-10T00:00:00"}