{"id":"https://openalex.org/W4200461846","doi":"https://doi.org/10.1109/wcsp52459.2021.9613660","title":"Fast Small Object Detection Algorithm Based on Feature Enhancement and Reconstruction","display_name":"Fast Small Object Detection Algorithm Based on Feature Enhancement and Reconstruction","publication_year":2021,"publication_date":"2021-10-20","ids":{"openalex":"https://openalex.org/W4200461846","doi":"https://doi.org/10.1109/wcsp52459.2021.9613660"},"language":"en","primary_location":{"id":"doi:10.1109/wcsp52459.2021.9613660","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wcsp52459.2021.9613660","pdf_url":null,"source":{"id":"https://openalex.org/S4363607893","display_name":"2021 13th International Conference on Wireless Communications and Signal Processing (WCSP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 13th International Conference on Wireless Communications and Signal Processing (WCSP)","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/A5018416684","display_name":"Zhiyong Huo","orcid":null},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyong Huo","raw_affiliation_strings":["College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010418146","display_name":"Tianwen Yan","orcid":null},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianwen Yan","raw_affiliation_strings":["College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082074822","display_name":"Weiye Cao","orcid":null},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiye Cao","raw_affiliation_strings":["College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I41198531"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.18195465,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9997000098228455,"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":0.9997000098228455,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9968000054359436,"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":0.9959999918937683,"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/computer-science","display_name":"Computer science","score":0.7695739269256592},{"id":"https://openalex.org/keywords/minimum-bounding-box","display_name":"Minimum bounding box","score":0.7000680565834045},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6981214284896851},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6165034770965576},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5854969620704651},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.560486912727356},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5565073490142822},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5534345507621765},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5222437977790833},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.4821128845214844},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.47975218296051025},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.47541743516921997},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.42863625288009644},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.41916540265083313},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.347635954618454},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.31498152017593384},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.10792091488838196}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7695739269256592},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.7000680565834045},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6981214284896851},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6165034770965576},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5854969620704651},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.560486912727356},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5565073490142822},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5534345507621765},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5222437977790833},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.4821128845214844},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.47975218296051025},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.47541743516921997},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.42863625288009644},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.41916540265083313},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.347635954618454},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.31498152017593384},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.10792091488838196},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wcsp52459.2021.9613660","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wcsp52459.2021.9613660","pdf_url":null,"source":{"id":"https://openalex.org/S4363607893","display_name":"2021 13th International Conference on Wireless Communications and Signal Processing (WCSP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 13th International Conference on Wireless Communications and Signal Processing (WCSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1536680647","https://openalex.org/W2102605133","https://openalex.org/W2476548250","https://openalex.org/W2570343428","https://openalex.org/W2752782242","https://openalex.org/W2963037989","https://openalex.org/W3011688396","https://openalex.org/W3013211776","https://openalex.org/W3016641475","https://openalex.org/W3019909811","https://openalex.org/W4293584584"],"related_works":["https://openalex.org/W3192357901","https://openalex.org/W3036286480","https://openalex.org/W2387360586","https://openalex.org/W4287027631","https://openalex.org/W4237171675","https://openalex.org/W2952736415","https://openalex.org/W3209723314","https://openalex.org/W3205398323","https://openalex.org/W2883297582","https://openalex.org/W2962677013"],"abstract_inverted_index":{"Small":[0],"object":[1],"detection":[2,39,60,95],"is":[3,41],"one":[4],"of":[5,14,28,36,58,93,105,134],"the":[6,12,24,26,32,37,45,56,91,100,112,117,123,132,135],"research":[7],"hotspots":[8],"and":[9,44,80,89,102,116],"challenges":[10],"in":[11,23,131],"field":[13],"machine":[15],"vision.":[16],"Because":[17],"small":[18,106],"targets":[19],"have":[20],"fewer":[21],"pixels":[22],"image,":[25],"number":[27],"features":[29],"captured":[30],"by":[31,127],"first":[33],"few":[34],"layers":[35],"target":[38,59],"network":[40,83],"very":[42],"small,":[43],"high-level":[46],"semantic":[47],"information":[48,88],"such":[49,143],"as":[50,144],"feature":[51,70,86],"classification":[52],"disappears":[53],"quickly,":[54],"making":[55],"accuracy":[57],"relatively":[61],"low.":[62],"The":[63,97],"paper":[64],"uses":[65,72,81],"sub-pixel":[66],"convolution":[67],"to":[68,77,84],"reconstruct":[69],"information,":[71],"SE":[73],"(Squeeze-and-Excitation)":[74],"attention":[75],"mechanism":[76],"enhance":[78],"features,":[79],"U-Net":[82],"capture":[85],"context":[87],"has":[90],"advantages":[92],"faster":[94],"speed.":[96],"algorithm":[98,124],"realizes":[99],"fast":[101],"accurate":[103],"identification":[104],"targets.":[107],"Numerical":[108],"experimental":[109],"results":[110],"on":[111],"COCO":[113],"data":[114,119],"set":[115,120],"SUN":[118],"show":[121],"that":[122],"improved":[125],"performance":[126],"more":[128],"than":[129],"12%":[130],"case":[133],"bounding":[136],"box":[137],"AP":[138],"compared":[139],"with":[140],"mainstream":[141],"algorithms":[142],"YOLOv4.":[145]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}