{"id":"https://openalex.org/W3115256228","doi":"https://doi.org/10.1145/3430199.3430236","title":"An Improved Method of Object Detection Based on Chip","display_name":"An Improved Method of Object Detection Based on Chip","publication_year":2020,"publication_date":"2020-06-26","ids":{"openalex":"https://openalex.org/W3115256228","doi":"https://doi.org/10.1145/3430199.3430236","mag":"3115256228"},"language":"en","primary_location":{"id":"doi:10.1145/3430199.3430236","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3430199.3430236","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 3rd International Conference on Artificial Intelligence and Pattern Recognition","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/A5084293354","display_name":"Jixin Wei","orcid":null},"institutions":[{"id":"https://openalex.org/I91125648","display_name":"Wuhan Institute of Technology","ror":"https://ror.org/04jcykh16","country_code":"CN","type":"education","lineage":["https://openalex.org/I91125648"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jixin Wei","raw_affiliation_strings":["Wuhan Institute of Technology, School of Computer Science and Engineering, Wuhan Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Wuhan Institute of Technology, School of Computer Science and Engineering, Wuhan Institute of Technology","institution_ids":["https://openalex.org/I91125648"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028317852","display_name":"Tongwei Lu","orcid":"https://orcid.org/0000-0002-3900-6456"},"institutions":[{"id":"https://openalex.org/I91125648","display_name":"Wuhan Institute of Technology","ror":"https://ror.org/04jcykh16","country_code":"CN","type":"education","lineage":["https://openalex.org/I91125648"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tongwei Lu","raw_affiliation_strings":["Wuhan Institute of Technology, School of Computer Science and Engineering, Wuhan Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Wuhan Institute of Technology, School of Computer Science and Engineering, Wuhan Institute of Technology","institution_ids":["https://openalex.org/I91125648"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072963539","display_name":"Zhimeng Xin","orcid":"https://orcid.org/0000-0002-0362-6979"},"institutions":[{"id":"https://openalex.org/I91125648","display_name":"Wuhan Institute of Technology","ror":"https://ror.org/04jcykh16","country_code":"CN","type":"education","lineage":["https://openalex.org/I91125648"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhimeng Xin","raw_affiliation_strings":["Wuhan Institute of Technology, School of Computer Science and Engineering, Wuhan Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Wuhan Institute of Technology, School of Computer Science and Engineering, Wuhan Institute of Technology","institution_ids":["https://openalex.org/I91125648"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5084293354"],"corresponding_institution_ids":["https://openalex.org/I91125648"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15495396,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"145","last_page":"151"},"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9991000294685364,"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"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9983000159263611,"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":0.7805162668228149},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.734230637550354},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6919496059417725},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.6901103258132935},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6873728036880493},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6289584040641785},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5996520519256592},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.591740071773529},{"id":"https://openalex.org/keywords/chip","display_name":"Chip","score":0.5863533020019531},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5182895064353943},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49933910369873047},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.49399715662002563},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.478153795003891},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4289090633392334},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12323397397994995},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.11246198415756226},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.06727039813995361}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7805162668228149},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.734230637550354},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6919496059417725},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.6901103258132935},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6873728036880493},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6289584040641785},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5996520519256592},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.591740071773529},{"id":"https://openalex.org/C165005293","wikidata":"https://www.wikidata.org/wiki/Q1074500","display_name":"Chip","level":2,"score":0.5863533020019531},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5182895064353943},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49933910369873047},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.49399715662002563},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.478153795003891},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4289090633392334},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12323397397994995},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.11246198415756226},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.06727039813995361},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3430199.3430236","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3430199.3430236","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 3rd International Conference on Artificial Intelligence and Pattern Recognition","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5252564012","display_name":null,"funder_award_id":"No.CX2019246","funder_id":"https://openalex.org/F4320325438","funder_display_name":"Wuhan Institute of Technology"}],"funders":[{"id":"https://openalex.org/F4320325438","display_name":"Wuhan Institute of Technology","ror":"https://ror.org/04jcykh16"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2109255472","https://openalex.org/W2565639579","https://openalex.org/W2570343428","https://openalex.org/W2591954064","https://openalex.org/W2613718673","https://openalex.org/W2804743778","https://openalex.org/W2962766617","https://openalex.org/W2963031226","https://openalex.org/W2963351448","https://openalex.org/W2963786238","https://openalex.org/W2968386350","https://openalex.org/W2968573796","https://openalex.org/W2990631821","https://openalex.org/W2991391304","https://openalex.org/W6751325469","https://openalex.org/W6967100175"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4285411112","https://openalex.org/W2085033728","https://openalex.org/W2171299904","https://openalex.org/W4390494008","https://openalex.org/W2922442631","https://openalex.org/W2053596378","https://openalex.org/W2168523118","https://openalex.org/W2073639911","https://openalex.org/W2969228573"],"abstract_inverted_index":{"In":[0],"spite":[1],"of":[2,18,86,116],"methods":[3],"for":[4,112],"object":[5,74],"detection":[6,75,123],"based":[7,77],"on":[8,78,127],"convolutional":[9,23],"neural":[10],"networks,":[11],"there's":[12],"a":[13,45,140],"problem":[14],"that":[15,32,63],"the":[16,22,34,42,50,105,109,114,132],"information":[17],"objects":[19],"missing":[20],"in":[21,37,49,104,144],"progress":[24,124],"with":[25],"an":[26,72],"immeasurable":[27],"proportion.":[28],"The":[29],"reason":[30],"is":[31,80,84],"while":[33],"network":[35],"downsample":[36],"order":[38],"to":[39,54],"further":[40],"obtain":[41],"abstract":[43],"features,":[44],"certain":[46],"pixel":[47],"point":[48],"feature":[51],"map":[52],"corresponding":[53],"more":[55],"original":[56],"image":[57],"area,":[58],"so":[59],"there're":[60],"less":[61],"content":[62],"can":[64],"be":[65],"referred":[66],"to.":[67],"To":[68],"handle":[69],"this":[70,137],"problem,":[71],"improved":[73],"method":[76,138],"YOLOv3":[79],"demonstrated.":[81],"Our":[82],"approach":[83],"composed":[85],"three":[87],"steps,":[88],"initial":[89],"detector,":[90],"adaptive":[91],"chip":[92,129],"generator,":[93],"secondary":[94],"detector.":[95],"Firstly,":[96],"figuring":[97],"out":[98],"which":[99],"chips":[100],"are":[101],"worth":[102],"detecting":[103],"image.":[106],"Secondly,":[107],"screening":[108],"best":[110],"associations":[111],"reduce":[113],"number":[115],"duplicate":[117],"detections":[118],"from":[119,135],"these":[120],"chips.":[121],"Finally,":[122],"will":[125],"run":[126],"each":[128],"and":[130,146],"summarize":[131],"output.":[133],"Benefit":[134],"it,":[136],"achieves":[139],"significant":[141],"performance":[142],"especially":[143],"medium":[145],"large":[147],"size":[148],"objects.":[149]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}