{"id":"https://openalex.org/W3129930510","doi":"https://doi.org/10.1109/igarss39084.2020.9323690","title":"Small Object Detection in Optical Remote Sensing Video with Motion Guided R-CNN","display_name":"Small Object Detection in Optical Remote Sensing Video with Motion Guided R-CNN","publication_year":2020,"publication_date":"2020-09-26","ids":{"openalex":"https://openalex.org/W3129930510","doi":"https://doi.org/10.1109/igarss39084.2020.9323690","mag":"3129930510"},"language":"en","primary_location":{"id":"doi:10.1109/igarss39084.2020.9323690","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss39084.2020.9323690","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"conference-paper","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/A5045546082","display_name":"Jie Feng","orcid":"https://orcid.org/0000-0002-8032-7542"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Feng","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015157242","display_name":"Yuping Liang","orcid":"https://orcid.org/0009-0001-0969-6038"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuping Liang","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020325182","display_name":"Zhanwei Ye","orcid":null},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhanwei Ye","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107790577","display_name":"Xiande Wu","orcid":"https://orcid.org/0000-0002-2272-1824"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiande Wu","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086657787","display_name":"Dening Zeng","orcid":null},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dening Zeng","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049776440","display_name":"Xiangrong Zhang","orcid":"https://orcid.org/0000-0003-0379-2042"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangrong Zhang","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059262797","display_name":"Xu Tang","orcid":"https://orcid.org/0000-0003-1375-0778"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Tang","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":0.4271,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.70426009,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"16","issue":null,"first_page":"272","last_page":"275"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9994000196456909,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9937999844551086,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/artificial-intelligence","display_name":"Artificial intelligence","score":0.8225290775299072},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7561625838279724},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6886538863182068},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6718844175338745},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6524494886398315},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.6302660703659058},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.5612176060676575},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5411168932914734},{"id":"https://openalex.org/keywords/motion-detection","display_name":"Motion detection","score":0.4980015754699707},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4641927480697632},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4395178258419037},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.43579694628715515},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42752254009246826}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8225290775299072},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7561625838279724},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6886538863182068},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6718844175338745},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6524494886398315},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.6302660703659058},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.5612176060676575},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5411168932914734},{"id":"https://openalex.org/C2780624872","wikidata":"https://www.wikidata.org/wiki/Q852453","display_name":"Motion detection","level":3,"score":0.4980015754699707},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4641927480697632},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4395178258419037},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.43579694628715515},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42752254009246826},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss39084.2020.9323690","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss39084.2020.9323690","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7099999785423279,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G4420409375","display_name":null,"funder_award_id":"LSIT201803D","funder_id":"https://openalex.org/F4320321133","funder_display_name":"Chinese Academy of Sciences"},{"id":"https://openalex.org/G8438634340","display_name":"\u57fa\u4e8e\u6df1\u5ea6\u5bf9\u6297\u7f51\u7edc\u548c\u5f3a\u5316\u5b66\u4e60\u7684\u9065\u611f\u89c6\u9891\u591a\u76ee\u6807\u68c0\u6d4b\u4e0e\u8ddf\u8e2a\u7814\u7a76","funder_award_id":"61871306","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/F4320321133","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2004506571","https://openalex.org/W2522520073","https://openalex.org/W2613718673","https://openalex.org/W2796347433","https://openalex.org/W2950141105","https://openalex.org/W2963179609","https://openalex.org/W2982770724","https://openalex.org/W2989604896","https://openalex.org/W3106250896","https://openalex.org/W4288325606","https://openalex.org/W4293584584","https://openalex.org/W6620707391","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W3162303681","https://openalex.org/W2911525783","https://openalex.org/W3204216905","https://openalex.org/W4376454785","https://openalex.org/W2559856295"],"abstract_inverted_index":{"Deep":[0],"learning":[1,143],"(DL)":[2],"based":[3],"object":[4],"detection":[5,19,138],"methods":[6],"have":[7],"been":[8],"making":[9],"great":[10],"achievements":[11],"for":[12,47],"natural":[13,28],"images,":[14,29],"which":[15,121],"guides":[16],"the":[17,56,80,100,123,133],"vehicle":[18],"of":[20,39,125],"optical":[21],"remote":[22],"sensing":[23],"videos":[24],"(ORSV).":[25],"Compared":[26],"with":[27],"objects":[30,53],"in":[31],"ORSV":[32,131],"are":[33,41,97],"smaller":[34],"and":[35,37,84],"blurrier,":[36],"most":[38],"vehicles":[40],"crowded.":[42],"Thus,":[43],"it":[44],"is":[45,68,77,115],"difficult":[46],"DL":[48],"to":[49,89],"detect":[50],"these":[51],"small":[52,109],"only":[54],"using":[55],"single-frame":[57],"image.":[58],"To":[59],"address":[60],"this":[61],"problem,":[62],"a":[63],"motion":[64,72],"guided":[65],"R-CNN":[66],"(MG-RCNN)":[67],"proposed.":[69],"In":[70],"MG-RCNN,":[71],"information":[73,88],"from":[74],"consecutive":[75],"frames":[76],"extracted":[78],"by":[79,103,117],"mean":[81],"differencing":[82],"method":[83,135],"merged":[85],"into":[86],"apparent":[87],"obtain":[90],"motion-related":[91],"discriminative":[92],"features.":[93],"Then,":[94],"high-quality":[95],"proposals":[96],"generated":[98],"on":[99,130],"feature":[101],"maps":[102],"mini-region":[104],"proposal":[105],"network":[106],"(MRPN).":[107],"For":[108],"targets,":[110],"an":[111],"improved":[112],"loss":[113],"function":[114],"defined":[116],"incorporating":[118],"smooth":[119],"factor,":[120],"makes":[122],"regression":[124],"shapes":[126],"more":[127],"stable.":[128],"Experiments":[129],"demonstrate":[132],"proposed":[134],"shows":[136],"superior":[137],"performance":[139],"over":[140],"state-of-the-art":[141],"deep":[142],"methods.":[144]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1}],"updated_date":"2026-08-06T08:24:18.245995","created_date":"2025-10-10T00:00:00"}
