{"id":"https://openalex.org/W2968261142","doi":"https://doi.org/10.1109/lgrs.2019.2930308","title":"Vehicle Detection in Remote Sensing Images Leveraging on Simultaneous Super-Resolution","display_name":"Vehicle Detection in Remote Sensing Images Leveraging on Simultaneous Super-Resolution","publication_year":2019,"publication_date":"2019-08-08","ids":{"openalex":"https://openalex.org/W2968261142","doi":"https://doi.org/10.1109/lgrs.2019.2930308","mag":"2968261142"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2019.2930308","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2019.2930308","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"]},{"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","SG"],"is_corresponding":false,"raw_author_name":"Zhi Gao","raw_affiliation_strings":["School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China","Temasek Laboratories, National University of Singapore, Singapore"],"raw_orcid":"https://orcid.org/0000-0003-3325-1183","affiliations":[{"raw_affiliation_string":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"Temasek Laboratories, National University of Singapore, 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/A5073814270","display_name":"Bharath Ramesh","orcid":"https://orcid.org/0000-0001-8230-3803"},"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":"Bharath Ramesh","raw_affiliation_strings":["Singapore Institute for Neurotechnology, National University of Singapore, Singapore"],"raw_orcid":"https://orcid.org/0000-0001-8230-3803","affiliations":[{"raw_affiliation_string":"Singapore Institute for Neurotechnology, National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]}],"institutions":[],"countries_distinct_count":2,"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":3.9803,"has_fulltext":false,"cited_by_count":86,"citation_normalized_percentile":{"value":0.95071377,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"17","issue":"4","first_page":"676","last_page":"680"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9998000264167786,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9998000264167786,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9952999949455261,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9943000078201294,"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":0.8543559312820435},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.7450240850448608},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6608380675315857},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6464359760284424},{"id":"https://openalex.org/keywords/generality","display_name":"Generality","score":0.5637195110321045},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5322605967521667},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5215411186218262},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43919435143470764},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.4259505569934845},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42556607723236084},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4206811785697937},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4120481312274933}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8543559312820435},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.7450240850448608},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6608380675315857},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6464359760284424},{"id":"https://openalex.org/C2780767217","wikidata":"https://www.wikidata.org/wiki/Q5532421","display_name":"Generality","level":2,"score":0.5637195110321045},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5322605967521667},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5215411186218262},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43919435143470764},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.4259505569934845},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42556607723236084},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4206811785697937},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4120481312274933},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2019.2930308","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2019.2930308","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":37,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1522301498","https://openalex.org/W1536680647","https://openalex.org/W1594676769","https://openalex.org/W1861492603","https://openalex.org/W1885185971","https://openalex.org/W2043552486","https://openalex.org/W2102605133","https://openalex.org/W2117539524","https://openalex.org/W2296151615","https://openalex.org/W2605995529","https://openalex.org/W2736200241","https://openalex.org/W2741137940","https://openalex.org/W2770937285","https://openalex.org/W2771079624","https://openalex.org/W2794849006","https://openalex.org/W2796347433","https://openalex.org/W2896155169","https://openalex.org/W2941333398","https://openalex.org/W2950800384","https://openalex.org/W2962903125","https://openalex.org/W2963372104","https://openalex.org/W2963470893","https://openalex.org/W2963606888","https://openalex.org/W2964121744","https://openalex.org/W3102192230","https://openalex.org/W3106250896","https://openalex.org/W4293418191","https://openalex.org/W4293584584","https://openalex.org/W6631190155","https://openalex.org/W6639102338","https://openalex.org/W6714138976","https://openalex.org/W6750161017","https://openalex.org/W6750227808","https://openalex.org/W6757422513","https://openalex.org/W6785652829","https://openalex.org/W6910796363"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3167935049","https://openalex.org/W3103566983","https://openalex.org/W3029198973","https://openalex.org/W2949096641","https://openalex.org/W2970686063"],"abstract_inverted_index":{"Owing":[0],"to":[1,16,66,88],"the":[2,22,32,40,53,78,84,99,106,125,136],"relatively":[3],"small":[4],"size":[5],"of":[6,43,56,101],"vehicles":[7,18],"in":[8,73],"remote":[9],"sensing":[10],"images,":[11],"lacking":[12],"sufficient":[13],"detailed":[14],"appearance":[15],"distinguish":[17],"from":[19,28],"similar":[20],"objects,":[21],"detection":[23,33,51,72,79],"performance":[24],"is":[25,81,95],"still":[26],"far":[27],"satisfactory":[29],"compared":[30],"with":[31],"results":[34],"on":[35,116],"everyday":[36],"images.":[37],"Inspired":[38],"by":[39],"positive":[41],"effects":[42],"super-resolution":[44],"convolutional":[45],"neural":[46],"network":[47,64],"(SRCNN)":[48],"for":[49],"object":[50],"and":[52,70,77,97,112],"stunning":[54],"success":[55],"deep":[57],"CNN":[58],"techniques,":[59],"we":[60],"apply":[61],"generative":[62],"adversarial":[63],"frameworks":[65],"realize":[67],"simultaneous":[68],"SRCNN":[69,85],"vehicle":[71],"an":[74],"end-to-end":[75],"manner,":[76],"loss":[80],"backpropagated":[82],"into":[83],"during":[86,105],"training":[87,107],"facilitate":[89],"detection.":[90],"In":[91],"particular,":[92],"our":[93,122],"work":[94],"unsupervised":[96],"bypasses":[98],"requirement":[100],"low-/high-resolution":[102],"image":[103],"pairs":[104],"stage,":[108],"achieving":[109],"increased":[110],"generality":[111],"applicability.":[113],"Extensive":[114],"experiments":[115],"representative":[117],"data":[118],"sets":[119],"demonstrate":[120],"that":[121],"method":[123],"outperforms":[124],"state-of-the-art":[126],"detectors.":[127],"(The":[128],"source":[129],"code":[130],"will":[131],"be":[132],"made":[133],"available":[134],"after":[135],"review":[137],"process).":[138]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":21},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":18},{"year":2020,"cited_by_count":10}],"updated_date":"2026-05-07T13:39:58.223016","created_date":"2025-10-10T00:00:00"}