{"id":"https://openalex.org/W7163045409","doi":"https://doi.org/10.13705/j.issn.1671-6833.2025.06.008","title":"Pointer Meter Reading Recognition Algorithm Based on Improved YOLOv8","display_name":"Pointer Meter Reading Recognition Algorithm Based on Improved YOLOv8","publication_year":2026,"publication_date":"2026-05-01","ids":{"openalex":"https://openalex.org/W7163045409","doi":"https://doi.org/10.13705/j.issn.1671-6833.2025.06.008"},"language":"zh","primary_location":{"id":"pmh:oai:doaj.org/article:66dda1942e234eadbfa3c441deaac6e3","doi":"https://doi.org/10.13705/j.issn.1671-6833.2025.06.008","is_oa":true,"landing_page_url":"https://doaj.org/article/66dda1942e234eadbfa3c441deaac6e3","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Zhengzhou Daxue xuebao. Gongxue ban, Vol 47, Iss 3, Pp 83-91 (2026)","raw_type":"article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["doaj"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doaj.org/article/66dda1942e234eadbfa3c441deaac6e3","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5127805793","display_name":"Z Z Zhang","orcid":"https://orcid.org/0000-0003-0739-1051","observed_orcids":["https://orcid.org/0000-0003-0739-1051","https://orcid.org/0009-0004-3457-5053","https://orcid.org/0009-0007-0752-7576"]},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"ZHANG Zhen","raw_affiliation_strings":["Henan Institute of Advanced Technology, Zhengzhou University, Zhengzhou 450001, China;School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, China;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Henan Institute of Advanced Technology, Zhengzhou University, Zhengzhou 450001, China;School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, China;","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104011994","display_name":"Liu Jianchang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"LIU Jianchang","raw_affiliation_strings":["Henan Institute of Advanced Technology, Zhengzhou University, Zhengzhou 450001, China;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Henan Institute of Advanced Technology, Zhengzhou University, Zhengzhou 450001, China;","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137548014","display_name":"GE Shuaibing","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"GE Shuaibing","raw_affiliation_strings":["Henan Institute of Advanced Technology, Zhengzhou University, Zhengzhou 450001, China;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Henan Institute of Advanced Technology, Zhengzhou University, Zhengzhou 450001, China;","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136892673","display_name":"ZHANG  Junjie","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"ZHANG Junjie","raw_affiliation_strings":["Henan Huirong Oil & Gas Technology Co., Ltd., Zhengzhou 450001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Henan Huirong Oil & Gas Technology Co., Ltd., Zhengzhou 450001, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5137601923","display_name":"ZHANG Kai","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"ZHANG Kai","raw_affiliation_strings":["Henan Huirong Oil & Gas Technology Co., Ltd., Zhengzhou 450001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Henan Huirong Oil & Gas Technology Co., Ltd., Zhengzhou 450001, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9580000042915344,"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":0.9580000042915344,"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":0.021199999377131462,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.004800000227987766,"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/yolov8","display_name":"YOLOv8","score":0.8650000095367432},{"id":"https://openalex.org/keywords/lightweight-object-detection","display_name":"lightweight object detection","score":0.796999990940094},{"id":"https://openalex.org/keywords/edge-devices","display_name":"edge devices","score":0.6169999837875366},{"id":"https://openalex.org/keywords/keypoint-detection","display_name":"keypoint detection","score":0.6759999990463257},{"id":"https://openalex.org/keywords/shape-iou-loss","display_name":"Shape-IoU loss","score":0.8980000019073486}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7275999784469604},{"id":"https://openalex.org/C150202949","wikidata":"https://www.wikidata.org/wiki/Q107602","display_name":"Pointer (user interface)","level":2,"score":0.5357000231742859},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5281999707221985},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49900001287460327},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.47369998693466187},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.43880000710487366},{"id":"https://openalex.org/C122383733","wikidata":"https://www.wikidata.org/wiki/Q865920","display_name":"Approximation error","level":2,"score":0.42980000376701355},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.413100004196167},{"id":"https://openalex.org/C93763578","wikidata":"https://www.wikidata.org/wiki/Q3503672","display_name":"Automatic meter reading","level":3,"score":0.3991999924182892},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.3644999861717224},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.33869999647140503},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33219999074935913},{"id":"https://openalex.org/C151011524","wikidata":"https://www.wikidata.org/wiki/Q11573","display_name":"Metre","level":2,"score":0.32749998569488525},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.3057999908924103},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.3057999908924103},{"id":"https://openalex.org/C3017489831","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Running time","level":2,"score":0.28790000081062317},{"id":"https://openalex.org/C554936623","wikidata":"https://www.wikidata.org/wiki/Q199657","display_name":"Reading (process)","level":2,"score":0.2815000116825104},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.27810001373291016},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.27480000257492065},{"id":"https://openalex.org/C158007255","wikidata":"https://www.wikidata.org/wiki/Q1055222","display_name":"Spectrum analyzer","level":2,"score":0.27140000462532043},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2669000029563904},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.2630999982357025}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:doaj.org/article:66dda1942e234eadbfa3c441deaac6e3","doi":"https://doi.org/10.13705/j.issn.1671-6833.2025.06.008","is_oa":true,"landing_page_url":"https://doaj.org/article/66dda1942e234eadbfa3c441deaac6e3","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Zhengzhou Daxue xuebao. Gongxue ban, Vol 47, Iss 3, Pp 83-91 (2026)","raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:doaj.org/article:66dda1942e234eadbfa3c441deaac6e3","doi":"https://doi.org/10.13705/j.issn.1671-6833.2025.06.008","is_oa":true,"landing_page_url":"https://doaj.org/article/66dda1942e234eadbfa3c441deaac6e3","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Zhengzhou Daxue xuebao. Gongxue ban, Vol 47, Iss 3, Pp 83-91 (2026)","raw_type":"article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4385241510","https://openalex.org/W4407278631","https://openalex.org/W4413923280","https://openalex.org/W4407475595","https://openalex.org/W4394773565","https://openalex.org/W4401596419","https://openalex.org/W4399994704","https://openalex.org/W4393206204","https://openalex.org/W4408609891","https://openalex.org/W7172313349"],"abstract_inverted_index":{"To":[0],"address":[1],"the":[2,19,50,60,64,74,88,92,95,101,111,118,133,151,195],"issues":[3],"of":[4,21,94,176,181],"existing":[5,193],"deep":[6],"learning-based":[7],"meter":[8,47,61],"reading":[9,65,202],"algorithms":[10],"on":[11],"edge":[12],"devices,":[13],"such":[14],"as":[15],"high":[16],"resource":[17],"consumption,":[18],"lack":[20],"robustness,":[22],"error":[23,175,180],"accumulation,":[24],"and":[25,63,76,97,140,146,158,164,186,201,204],"difficulty":[26],"in":[27,31,36],"end-to-end":[28],"pointer":[29,75],"extraction":[30],"traditional":[32],"image":[33],"processing":[34],"methods":[35],"complex":[37,168],"scenarios,":[38,169],"a":[39,80],"lightweight":[40,81],"improved":[41,134,205],"YOLOv8":[42],"model":[43,53,136,159],"was":[44,54,66,84,123],"proposed":[45,196],"for":[46],"detection.":[48],"Meanwhile,":[49],"YOLOv8-pose":[51],"keypoint":[52],"employed":[55],"to":[56,86,125],"extract":[57],"keypoints":[58],"from":[59],"dial,":[62],"calculated":[67],"using":[68],"an":[69,172],"angle-based":[70],"method":[71],"by":[72,161],"fitting":[73],"scale":[77],"lines.":[78],"Firstly,":[79],"RGELAN":[82],"module":[83],"designed":[85],"replace":[87],"C2f":[89],"module,":[90],"reducing":[91,114,155],"complexity":[93],"backbone":[96],"neck":[98],"networks.":[99],"Then,":[100],"CASC-Head":[102],"detection":[103,115,127,206],"head,":[104,113],"which":[105],"considered":[106],"multi-scale":[107],"feature":[108],"contributions,":[109],"replaced":[110],"decoupled":[112],"parameters.":[116],"Finally,":[117],"Shape-IoU":[119],"optimized":[120],"regression":[121],"loss":[122],"introduced":[124],"improve":[126],"accuracy.":[128],"Experimental":[129],"results":[130],"showed":[131],"that":[132],"YOLOv8-RSS":[135],"achieved":[137,171],"98.5%":[138],"precision":[139],"90.6%":[141],"mAP@50:95,":[142],"with":[143,150,192],"only":[144],"0.3%":[145],"0.4%":[147],"losses":[148],"compared":[149],"original":[152],"YOLOv8,":[153],"while":[154],"parameters,":[156,185],"computation,":[157],"size":[160],"48.3%,":[162],"44.4%,":[163],"46%,":[165],"respectively.":[166],"In":[167],"it":[170],"average":[173,178],"relative":[174],"1.425%,":[177],"absolute":[179],"0.557%,":[182],"3.08":[183],"MB":[184],"78":[187],"frame":[188],"per":[189],"second.":[190],"Compared":[191],"methods,":[194],"algorithm":[197],"reduced":[198],"space":[199],"consumption":[200],"errors,":[203],"speed.":[207]},"counts_by_year":[],"updated_date":"2026-10-12T09:40:04.860316","created_date":"2026-06-02T00:00:00"}