{"id":"https://openalex.org/W3034465353","doi":"https://doi.org/10.1109/icme46284.2020.9102807","title":"Cascade Detector With Feature Fusion For Arbitrary-Oriented Objects In Remote Sensing Images","display_name":"Cascade Detector With Feature Fusion For Arbitrary-Oriented Objects In Remote Sensing Images","publication_year":2020,"publication_date":"2020-06-09","ids":{"openalex":"https://openalex.org/W3034465353","doi":"https://doi.org/10.1109/icme46284.2020.9102807","mag":"3034465353"},"language":"en","primary_location":{"id":"doi:10.1109/icme46284.2020.9102807","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme46284.2020.9102807","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-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/A5031457689","display_name":"Liping Hou","orcid":"https://orcid.org/0000-0002-4984-3290"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Liping Hou","raw_affiliation_strings":["School of Engineering Science, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Engineering Science, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072833759","display_name":"Ke L\u00fc","orcid":"https://orcid.org/0000-0003-0176-3088"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ke Lu","raw_affiliation_strings":["School of Engineering Science, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Engineering Science, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100763213","display_name":"Jian Xue","orcid":"https://orcid.org/0000-0002-9460-802X"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Xue","raw_affiliation_strings":["School of Engineering Science, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Engineering Science, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100324585","display_name":"Hao Li","orcid":"https://orcid.org/0000-0002-9045-561X"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Hao","raw_affiliation_strings":["School of Engineering Science, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Engineering Science, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5031457689"],"corresponding_institution_ids":["https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":2.4425,"has_fulltext":false,"cited_by_count":40,"citation_normalized_percentile":{"value":0.90853331,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9993000030517578,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9993000030517578,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9984999895095825,"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":0.7973824739456177},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.7105588316917419},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7075556516647339},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6464942097663879},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6218271255493164},{"id":"https://openalex.org/keywords/subnet","display_name":"Subnet","score":0.6093316674232483},{"id":"https://openalex.org/keywords/cascade","display_name":"Cascade","score":0.5986360311508179},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5942082405090332},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5042589902877808},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4721044600009918},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.44967228174209595},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4174843728542328},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36311501264572144},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.12326133251190186},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0973585844039917}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7973824739456177},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.7105588316917419},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7075556516647339},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6464942097663879},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6218271255493164},{"id":"https://openalex.org/C21099817","wikidata":"https://www.wikidata.org/wiki/Q7631721","display_name":"Subnet","level":2,"score":0.6093316674232483},{"id":"https://openalex.org/C34146451","wikidata":"https://www.wikidata.org/wiki/Q5048094","display_name":"Cascade","level":2,"score":0.5986360311508179},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5942082405090332},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5042589902877808},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4721044600009918},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.44967228174209595},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4174843728542328},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36311501264572144},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.12326133251190186},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0973585844039917},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C42360764","wikidata":"https://www.wikidata.org/wiki/Q83588","display_name":"Chemical engineering","level":1,"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme46284.2020.9102807","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme46284.2020.9102807","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W1861492603","https://openalex.org/W2031489346","https://openalex.org/W2565639579","https://openalex.org/W2570343428","https://openalex.org/W2593539516","https://openalex.org/W2613718673","https://openalex.org/W2725486421","https://openalex.org/W2796347433","https://openalex.org/W2804523038","https://openalex.org/W2808360995","https://openalex.org/W2855340099","https://openalex.org/W2900572491","https://openalex.org/W2922509574","https://openalex.org/W2962721361","https://openalex.org/W2962749812","https://openalex.org/W2963037989","https://openalex.org/W2963351448","https://openalex.org/W2964979676","https://openalex.org/W2967487473","https://openalex.org/W3098218837","https://openalex.org/W3106228955","https://openalex.org/W3106250896","https://openalex.org/W4293584584","https://openalex.org/W4297803092","https://openalex.org/W6620707391","https://openalex.org/W6639102338","https://openalex.org/W6739844568","https://openalex.org/W6750227808","https://openalex.org/W6753033036","https://openalex.org/W6755677541","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W2102539527","https://openalex.org/W2356206668","https://openalex.org/W2131631951","https://openalex.org/W2130707537","https://openalex.org/W2105155969","https://openalex.org/W1977409556","https://openalex.org/W2361602549","https://openalex.org/W4362683600","https://openalex.org/W3200778902","https://openalex.org/W2390667963"],"abstract_inverted_index":{"Detection":[0],"of":[1,15,25,114],"multi-class":[2],"rotated":[3,61],"objects":[4,43,62,94],"is":[5,73,87,118],"a":[6,69,82,112,125],"challenging":[7],"task":[8],"in":[9,44,63,92],"optical":[10],"remote":[11,45,65,128],"sensing":[12,46,66,129],"images":[13],"because":[14],"large-scale":[16],"variations,":[17],"arbitrary":[18],"orientations":[19],"and":[20,101],"complex":[21,64,96],"backgrounds,":[22],"etc.":[23],"Most":[24],"the":[26],"state-of-the-art":[27,142],"object":[28,103,110,135],"detectors":[29],"for":[30,41],"natural":[31],"images,":[32],"that":[33,57,133],"use":[34],"horizontal":[35],"bounding":[36],"boxes,":[37],"are":[38],"not":[39],"suitable":[40],"oriented":[42],"images.":[47,67],"In":[48],"this":[49],"paper,":[50],"we":[51],"propose":[52],"an":[53],"end-to-end":[54],"cascade":[55,113],"detector":[56,136],"can":[58],"effectively":[59],"detect":[60],"Specifically,":[68],"feature":[70],"fusion":[71],"block":[72],"designed":[74],"to":[75,89,106,120],"capture":[76],"features":[77],"with":[78,95],"more":[79,108],"details.":[80],"Meanwhile,":[81],"supervised":[83],"spatial":[84],"attention":[85],"mechanism":[86],"adopted":[88],"improve":[90],"performance":[91,139],"detecting":[93],"backgrounds":[97],"by":[98],"weakening":[99],"noise":[100],"enhancing":[102],"regions.":[104],"Finally,":[105],"obtain":[107],"accurate":[109],"position,":[111],"multi-step":[115],"detection":[116],"subnet":[117],"implemented":[119],"refine":[121],"anchors.":[122],"Experiments":[123],"using":[124],"publicly":[126],"available":[127],"dataset":[130],"DOTA":[131],"show":[132],"our":[134],"achieves":[137],"superior":[138],"over":[140],"other":[141],"approaches.":[143]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}