{"id":"https://openalex.org/W2664380602","doi":"https://doi.org/10.1109/lgrs.2017.2708722","title":"M-FCN: Effective Fully Convolutional Network-Based Airplane Detection Framework","display_name":"M-FCN: Effective Fully Convolutional Network-Based Airplane Detection Framework","publication_year":2017,"publication_date":"2017-06-22","ids":{"openalex":"https://openalex.org/W2664380602","doi":"https://doi.org/10.1109/lgrs.2017.2708722","mag":"2664380602"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2017.2708722","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2017.2708722","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-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/A5102824683","display_name":"Yiding Yang","orcid":"https://orcid.org/0000-0001-8290-9805"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiding Yang","raw_affiliation_strings":["Beijing Key Laboratory of Embedded Real-time Information Processing Technology, Radar Research Laboratory, School of Information and Electronic, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8290-9805","affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Embedded Real-time Information Processing Technology, Radar Research Laboratory, School of Information and Electronic, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023179941","display_name":"Yin Zhuang","orcid":"https://orcid.org/0000-0002-0443-1081"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yin Zhuang","raw_affiliation_strings":["Beijing Key Laboratory of Embedded Real-time Information Processing Technology, Radar Research Laboratory, School of Information and Electronic, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0443-1081","affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Embedded Real-time Information Processing Technology, Radar Research Laboratory, School of Information and Electronic, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022557444","display_name":"Fukun Bi","orcid":"https://orcid.org/0000-0003-3501-9142"},"institutions":[{"id":"https://openalex.org/I1456306","display_name":"North China University of Technology","ror":"https://ror.org/01nky7652","country_code":"CN","type":"education","lineage":["https://openalex.org/I1456306"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fukun Bi","raw_affiliation_strings":["School of Electronic Information Engineering, North China University of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Information Engineering, North China University of Technology, Beijing, China","institution_ids":["https://openalex.org/I1456306"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085178924","display_name":"Hao Shi","orcid":"https://orcid.org/0000-0002-2013-6592"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Shi","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-2013-6592","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014833698","display_name":"Yizhuang Xie","orcid":"https://orcid.org/0000-0003-1312-2691"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yizhuang Xie","raw_affiliation_strings":["Beijing Key Laboratory of Embedded Real-time Information Processing Technology, Radar Research Laboratory, School of Information and Electronic, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-1312-2691","affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Embedded Real-time Information Processing Technology, Radar Research Laboratory, School of Information and Electronic, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.5686,"has_fulltext":false,"cited_by_count":53,"citation_normalized_percentile":{"value":0.92662174,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"14","issue":"8","first_page":"1293","last_page":"1297"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9986000061035156,"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/T13282","display_name":"Automated Road and Building Extraction","score":0.9973000288009644,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7715334892272949},{"id":"https://openalex.org/keywords/markov-random-field","display_name":"Markov random field","score":0.7237707376480103},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6398241519927979},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.622662365436554},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5244524478912354},{"id":"https://openalex.org/keywords/airplane","display_name":"Airplane","score":0.5121731758117676},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.46267837285995483},{"id":"https://openalex.org/keywords/cascade","display_name":"Cascade","score":0.4261261522769928},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.18362247943878174},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.09618470072746277}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7715334892272949},{"id":"https://openalex.org/C2778045648","wikidata":"https://www.wikidata.org/wiki/Q176827","display_name":"Markov random field","level":4,"score":0.7237707376480103},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6398241519927979},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.622662365436554},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5244524478912354},{"id":"https://openalex.org/C2781407631","wikidata":"https://www.wikidata.org/wiki/Q197","display_name":"Airplane","level":2,"score":0.5121731758117676},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.46267837285995483},{"id":"https://openalex.org/C34146451","wikidata":"https://www.wikidata.org/wiki/Q5048094","display_name":"Cascade","level":2,"score":0.4261261522769928},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.18362247943878174},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.09618470072746277},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2017.2708722","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2017.2708722","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7022816921","display_name":null,"funder_award_id":"61601006","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"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1903029394","https://openalex.org/W2005368619","https://openalex.org/W2020999234","https://openalex.org/W2064094295","https://openalex.org/W2088049833","https://openalex.org/W2186615578","https://openalex.org/W2245000483","https://openalex.org/W2270801692","https://openalex.org/W2308318555","https://openalex.org/W2407521645","https://openalex.org/W2412558220","https://openalex.org/W2512351403","https://openalex.org/W2950800384","https://openalex.org/W6714138976"],"related_works":["https://openalex.org/W3021491005","https://openalex.org/W2153719181","https://openalex.org/W2188789443","https://openalex.org/W2315699100","https://openalex.org/W323439142","https://openalex.org/W1971748923","https://openalex.org/W2070939993","https://openalex.org/W2060986072","https://openalex.org/W1566155057","https://openalex.org/W2381008430"],"abstract_inverted_index":{"Airplane":[0],"detection":[1,17],"is":[2,26,65,77,81,101,141],"a":[3,31,43,54,73,109,136],"challenging":[4],"problem":[5],"in":[6],"complex":[7],"remote":[8],"sensing":[9],"imaging.":[10],"In":[11,58,132],"this":[12],"letter,":[13],"an":[14,37],"effective":[15],"airplane":[16],"framework":[18],"called":[19],"Markov":[20],"random":[21,45],"field-fully":[22],"convolutional":[23,137],"network":[24],"(M-FCN)":[25],"proposed.":[27],"The":[28],"M-FCN":[29,155],"uses":[30],"cascade":[32],"strategy":[33,123],"that":[34,153],"consists":[35],"of":[36,147],"FCN-based":[38],"coarse":[39,74,98],"candidate":[40,75,99],"extraction":[41],"stage,":[42,52,61,96,135],"multi-Markov":[44],"field":[46,107],"(multi-MRF)-based":[47],"region":[48],"proposal":[49],"(RP)":[50],"generation":[51],"and":[53,72,84,86,112,160],"final":[55],"classification":[56],"stage.":[57],"the":[59,62,94,97,104,118,133,145,148,154],"first":[60,95],"FCN":[63],"model":[64,80],"trained":[66],"to":[67,70,117,143],"be":[68],"sensitive":[69],"airplanes,":[71],"map":[76,100],"generated.":[78],"This":[79,121],"scale-,":[82],"direction-,":[83],"color-invariant":[85],"does":[87],"not":[88],"require":[89],"many":[90],"training":[91],"examples.":[92],"After":[93],"used":[102,142],"as":[103],"initial":[105],"labeling":[106],"for":[108],"multi-MRF":[110,119],"algorithm,":[111],"RPs":[113],"are":[114],"generated":[115],"according":[116],"output.":[120],"RP-generating":[122],"can":[124],"yield":[125],"more":[126],"accurate":[127],"locations":[128],"with":[129],"fewer":[130],"RPs.":[131],"last":[134],"neural":[138],"network-based":[139],"classifier":[140],"improve":[144],"precision":[146],"entire":[149],"framework.":[150],"Experiments":[151],"show":[152],"has":[156],"high":[157],"precision,":[158],"recall,":[159],"location":[161],"accuracy.":[162]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":11},{"year":2018,"cited_by_count":7},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}