{"id":"https://openalex.org/W3013687099","doi":"https://doi.org/10.1145/3373509.3373528","title":"Object Detection Based on Feature Scale Fusion and Feature Scale Enhancement","display_name":"Object Detection Based on Feature Scale Fusion and Feature Scale Enhancement","publication_year":2019,"publication_date":"2019-10-23","ids":{"openalex":"https://openalex.org/W3013687099","doi":"https://doi.org/10.1145/3373509.3373528","mag":"3013687099"},"language":"en","primary_location":{"id":"doi:10.1145/3373509.3373528","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3373509.3373528","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 8th International Conference on Computing and Pattern Recognition","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/A5100378601","display_name":"Jing Wang","orcid":"https://orcid.org/0000-0002-8491-4146"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Wang","raw_affiliation_strings":["College of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021166773","display_name":"Ping Gong","orcid":"https://orcid.org/0000-0002-4782-1741"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ping Gong","raw_affiliation_strings":["College of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100702698","display_name":"Ziyuan Liu","orcid":"https://orcid.org/0000-0001-7164-088X"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziyuan Liu","raw_affiliation_strings":["College of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.21985024,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2006","issue":null,"first_page":"106","last_page":"111"},"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9976000189781189,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9934999942779541,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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":0.7770155668258667},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7570468187332153},{"id":"https://openalex.org/keywords/pascal","display_name":"Pascal (unit)","score":0.7060261368751526},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6820215582847595},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6737855672836304},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.641602635383606},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.5692077875137329},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5514560341835022},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5512403845787048},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.45594510436058044},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.4468840956687927},{"id":"https://openalex.org/keywords/feature-detection","display_name":"Feature detection (computer vision)","score":0.4263328015804291},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.42616182565689087},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3329213857650757},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.24133917689323425}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7770155668258667},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7570468187332153},{"id":"https://openalex.org/C75608658","wikidata":"https://www.wikidata.org/wiki/Q44395","display_name":"Pascal (unit)","level":2,"score":0.7060261368751526},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6820215582847595},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6737855672836304},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.641602635383606},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.5692077875137329},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5514560341835022},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5512403845787048},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.45594510436058044},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.4468840956687927},{"id":"https://openalex.org/C126422989","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature detection (computer vision)","level":4,"score":0.4263328015804291},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.42616182565689087},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3329213857650757},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.24133917689323425},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3373509.3373528","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3373509.3373528","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 8th International Conference on Computing and Pattern Recognition","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.4099999964237213}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W1923697677","https://openalex.org/W1948751323","https://openalex.org/W2088049833","https://openalex.org/W2097117768","https://openalex.org/W2102605133","https://openalex.org/W2134927309","https://openalex.org/W2150134853","https://openalex.org/W2163605009","https://openalex.org/W2193145675","https://openalex.org/W2194775991","https://openalex.org/W2395611524","https://openalex.org/W2412782625","https://openalex.org/W2476548250","https://openalex.org/W2490270993","https://openalex.org/W2565639579","https://openalex.org/W2768489488","https://openalex.org/W2962992847","https://openalex.org/W3106250896"],"related_works":["https://openalex.org/W4376620596","https://openalex.org/W3177249605","https://openalex.org/W2534152068","https://openalex.org/W3138508047","https://openalex.org/W1972515067","https://openalex.org/W1689909837","https://openalex.org/W4293054914","https://openalex.org/W4298525700","https://openalex.org/W2953362004","https://openalex.org/W2549121492"],"abstract_inverted_index":{"Currently,":[0],"object":[1,47,64],"detection":[2,48,65,149],"is":[3,14,49,129,139],"widely":[4],"used":[5],"to":[6,28,38,95,141],"deal":[7],"with":[8,67],"the":[9,15,23,33,41,50,59,96,106,111,126,132,146],"image":[10,25,35,51],"analysis":[11],"problem,":[12],"which":[13,138],"most":[16,147],"important":[17],"task":[18],"in":[19],"computer":[20],"version.":[21],"As":[22],"high":[24,29],"resolution":[26,36,52],"leads":[27,37],"computational":[30],"cost":[31],"and":[32,71,89,116,135],"low":[34,39],"accuracy,":[40],"key":[42],"bottleneck":[43],"of":[44,61,100,113,119,125],"CNN":[45],"based":[46],"selection.":[53],"In":[54,103],"this":[55,104],"work,":[56],"we":[57],"solve":[58],"problem":[60],"obtaining":[62],"powerful":[63],"effect":[66],"feature":[68,72,97,108],"scale":[69,73],"fusion":[70],"enhancement.":[74],"The":[75,122],"proposed":[76],"module":[77,128],"can":[78],"achieve":[79],"significant":[80,143],"accuracy":[81,123],"by":[82],"applying":[83],"Feature":[84,90],"Scale":[85,91],"Fusion":[86],"Module":[87,93],"(FSFM)":[88],"Enhancement":[92],"(FSEM)":[94],"extraction":[98],"layer":[99,115,118],"Faster":[101,120],"R-CNN.":[102,121],"case,":[105],"enhanced":[107],"map":[109],"become":[110],"input":[112],"RPN":[114],"ROI":[117],"gain":[124],"propose":[127],"verified":[130],"via":[131],"Pascal":[133],"VOC":[134],"MSCOCO":[136],"datasets,":[137],"proved":[140],"obtain":[142],"improvements":[144],"over":[145],"advanced":[148],"models.":[150]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
