{"id":"https://openalex.org/W2941333398","doi":"https://doi.org/10.1109/lgrs.2019.2909541","title":"Improved Faster R-CNN With Multiscale Feature Fusion and Homography Augmentation for Vehicle Detection in Remote Sensing Images","display_name":"Improved Faster R-CNN With Multiscale Feature Fusion and Homography Augmentation for Vehicle Detection in Remote Sensing Images","publication_year":2019,"publication_date":"2019-04-25","ids":{"openalex":"https://openalex.org/W2941333398","doi":"https://doi.org/10.1109/lgrs.2019.2909541","mag":"2941333398"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2019.2909541","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2019.2909541","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/A5004950171","display_name":"Hong Ji","orcid":"https://orcid.org/0000-0003-0812-4334"},"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":"Hong Ji","raw_affiliation_strings":["Electronic and Information School, Wuhan University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electronic and Information School, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084683976","display_name":"Zhi Gao","orcid":"https://orcid.org/0000-0003-3325-1183"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Zhi Gao","raw_affiliation_strings":["Temasek Laboratories, National University of Singapore"],"raw_orcid":"https://orcid.org/0000-0003-3325-1183","affiliations":[{"raw_affiliation_string":"Temasek Laboratories, National University of Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022219449","display_name":"Tiancan Mei","orcid":"https://orcid.org/0000-0003-4166-7891"},"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":"Tiancan Mei","raw_affiliation_strings":["Electronic and Information School, Wuhan University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electronic and Information School, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100427048","display_name":"Yifan Li","orcid":"https://orcid.org/0000-0002-9526-2243"},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"education","lineage":["https://openalex.org/I204512498"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Yifan Li","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Macau, Macau, China"],"raw_orcid":"https://orcid.org/0000-0002-9526-2243","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Macau, Macau, China","institution_ids":["https://openalex.org/I204512498"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5004950171"],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":null,"apc_paid":null,"fwci":3.0633,"has_fulltext":false,"cited_by_count":49,"citation_normalized_percentile":{"value":0.93374425,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"16","issue":"11","first_page":"1761","last_page":"1765"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":1.0,"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":1.0,"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":0.9986000061035156,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9948999881744385,"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":0.8351618051528931},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7198987007141113},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6972545385360718},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6628279685974121},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6536448001861572},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6426736116409302},{"id":"https://openalex.org/keywords/homography","display_name":"Homography","score":0.589046835899353},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5860981345176697},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.46092769503593445},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4524366855621338},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.45054376125335693},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44072359800338745},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.43427878618240356},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2833144962787628}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8351618051528931},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7198987007141113},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6972545385360718},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6628279685974121},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6536448001861572},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6426736116409302},{"id":"https://openalex.org/C28751775","wikidata":"https://www.wikidata.org/wiki/Q2112539","display_name":"Homography","level":4,"score":0.589046835899353},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5860981345176697},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.46092769503593445},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4524366855621338},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.45054376125335693},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44072359800338745},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.43427878618240356},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2833144962787628},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"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},{"id":"https://openalex.org/C177846678","wikidata":"https://www.wikidata.org/wiki/Q1501864","display_name":"Projective test","level":2,"score":0.0},{"id":"https://openalex.org/C75280867","wikidata":"https://www.wikidata.org/wiki/Q877775","display_name":"Projective space","level":3,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C11171543","wikidata":"https://www.wikidata.org/wiki/Q41630","display_name":"Psychoanalysis","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2019.2909541","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2019.2909541","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":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W1594676769","https://openalex.org/W2043552486","https://openalex.org/W2064022862","https://openalex.org/W2095537868","https://openalex.org/W2102605133","https://openalex.org/W2102673432","https://openalex.org/W2145717442","https://openalex.org/W2176924101","https://openalex.org/W2194775991","https://openalex.org/W2343118941","https://openalex.org/W2565639579","https://openalex.org/W2587248218","https://openalex.org/W2605995529","https://openalex.org/W2606788270","https://openalex.org/W2613825824","https://openalex.org/W2735165202","https://openalex.org/W2736200241","https://openalex.org/W2770937285","https://openalex.org/W2771079624","https://openalex.org/W2772452219","https://openalex.org/W2796347433","https://openalex.org/W2804532080","https://openalex.org/W2887463361","https://openalex.org/W3102192230","https://openalex.org/W3104282073","https://openalex.org/W4293584584"],"related_works":["https://openalex.org/W2771220351","https://openalex.org/W67284269","https://openalex.org/W2182457744","https://openalex.org/W2499396280","https://openalex.org/W2913302899","https://openalex.org/W2900568167","https://openalex.org/W2546942002","https://openalex.org/W2382607599","https://openalex.org/W4320802741","https://openalex.org/W4281689716"],"abstract_inverted_index":{"Vehicle":[0],"detection":[1,45,73,89],"in":[2,14,19,43,74],"remote":[3,75,82],"sensing":[4,76,83],"images":[5],"has":[6],"attracted":[7],"remarkable":[8],"attention":[9],"for":[10],"its":[11],"important":[12],"role":[13],"a":[15],"variety":[16],"of":[17,30],"applications":[18],"traffic,":[20],"security,":[21],"and":[22,66],"military":[23],"fields.":[24],"Motivated":[25],"by":[26],"the":[27,40,55,98,109],"stunning":[28],"success":[29],"region":[31],"convolutional":[32],"neural":[33],"network":[34],"(R-CNN)":[35],"techniques,":[36],"which":[37],"have":[38],"achieved":[39],"state-of-the-art":[41,99],"performance":[42,96],"object":[44],"task":[46],"on":[47,80],"benchmark":[48],"data":[49,68,84],"sets,":[50],"we":[51],"propose":[52],"to":[53,70,87],"improve":[54],"Faster":[56],"R-CNN":[57],"method":[58,93],"with":[59],"better":[60,95],"feature":[61,64],"extraction,":[62],"multiscale":[63],"fusion,":[65],"homography":[67],"augmentation":[69],"realize":[71],"vehicle":[72,88],"images.":[77],"Extensive":[78],"experiments":[79],"representative":[81],"sets":[85],"related":[86],"demonstrate":[90],"that":[91],"our":[92],"achieves":[94],"than":[97],"approaches.":[100],"The":[101],"source":[102],"code":[103],"will":[104],"be":[105],"made":[106],"available":[107],"(after":[108],"review":[110],"process).":[111]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
