{"id":"https://openalex.org/W7127938289","doi":"https://doi.org/10.1109/iccma67641.2025.11369653","title":"Research on an Automated Detection Method for Dental Needles Based on Direction-Adaptive Convolution","display_name":"Research on an Automated Detection Method for Dental Needles Based on Direction-Adaptive Convolution","publication_year":2025,"publication_date":"2025-11-24","ids":{"openalex":"https://openalex.org/W7127938289","doi":"https://doi.org/10.1109/iccma67641.2025.11369653"},"language":null,"primary_location":{"id":"doi:10.1109/iccma67641.2025.11369653","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccma67641.2025.11369653","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 13th International Conference on Control, Mechatronics and Automation (ICCMA)","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/A5125215802","display_name":"Xiangyao Li","orcid":null},"institutions":[{"id":"https://openalex.org/I187175081","display_name":"Shaanxi University of Technology","ror":"https://ror.org/056m91h77","country_code":"CN","type":"education","lineage":["https://openalex.org/I187175081"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangyao Li","raw_affiliation_strings":["Shanxi University of Technology,School of Mechanical Engineering,HanZhong,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanxi University of Technology,School of Mechanical Engineering,HanZhong,China","institution_ids":["https://openalex.org/I187175081"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047181862","display_name":"Hongling Hou","orcid":"https://orcid.org/0000-0002-0902-7395"},"institutions":[{"id":"https://openalex.org/I187175081","display_name":"Shaanxi University of Technology","ror":"https://ror.org/056m91h77","country_code":"CN","type":"education","lineage":["https://openalex.org/I187175081"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongling Hou","raw_affiliation_strings":["Shanxi University of Technology,School of Mechanical Engineering,HanZhong,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanxi University of Technology,School of Mechanical Engineering,HanZhong,China","institution_ids":["https://openalex.org/I187175081"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104086200","display_name":"Jianqiang Jin","orcid":null},"institutions":[{"id":"https://openalex.org/I187175081","display_name":"Shaanxi University of Technology","ror":"https://ror.org/056m91h77","country_code":"CN","type":"education","lineage":["https://openalex.org/I187175081"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianqiang Jin","raw_affiliation_strings":["Shanxi University of Technology,School of Mechanical Engineering,HanZhong,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanxi University of Technology,School of Mechanical Engineering,HanZhong,China","institution_ids":["https://openalex.org/I187175081"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071817986","display_name":"Qiankun Ju","orcid":null},"institutions":[{"id":"https://openalex.org/I187175081","display_name":"Shaanxi University of Technology","ror":"https://ror.org/056m91h77","country_code":"CN","type":"education","lineage":["https://openalex.org/I187175081"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiankun Ju","raw_affiliation_strings":["Shanxi University of Technology,School of Mechanical Engineering,HanZhong,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanxi University of Technology,School of Mechanical Engineering,HanZhong,China","institution_ids":["https://openalex.org/I187175081"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5125126641","display_name":"Yanyan Bian","orcid":null},"institutions":[{"id":"https://openalex.org/I187175081","display_name":"Shaanxi University of Technology","ror":"https://ror.org/056m91h77","country_code":"CN","type":"education","lineage":["https://openalex.org/I187175081"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanyan Bian","raw_affiliation_strings":["Shanxi University of Technology,School of Mechanical Engineering,HanZhong,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanxi University of Technology,School of Mechanical Engineering,HanZhong,China","institution_ids":["https://openalex.org/I187175081"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I187175081"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.64724409,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"582","last_page":"586"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11363","display_name":"Dental Radiography and Imaging","score":0.40549999475479126,"subfield":{"id":"https://openalex.org/subfields/3504","display_name":"Oral Surgery"},"field":{"id":"https://openalex.org/fields/35","display_name":"Dentistry"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11363","display_name":"Dental Radiography and Imaging","score":0.40549999475479126,"subfield":{"id":"https://openalex.org/subfields/3504","display_name":"Oral Surgery"},"field":{"id":"https://openalex.org/fields/35","display_name":"Dentistry"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.1363999992609024,"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/T12439","display_name":"Dental Research and COVID-19","score":0.03550000116229057,"subfield":{"id":"https://openalex.org/subfields/3500","display_name":"General Dentistry"},"field":{"id":"https://openalex.org/fields/35","display_name":"Dentistry"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.7281000018119812},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5667999982833862},{"id":"https://openalex.org/keywords/orientation","display_name":"Orientation (vector space)","score":0.510200023651123},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.49790000915527344},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.4666000008583069},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4474000036716461},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.420199990272522},{"id":"https://openalex.org/keywords/geometric-transformation","display_name":"Geometric transformation","score":0.41269999742507935}],"concepts":[{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.7281000018119812},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6951000094413757},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6855000257492065},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6154999732971191},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5667999982833862},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.510200023651123},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.49790000915527344},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.4666000008583069},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4474000036716461},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.420199990272522},{"id":"https://openalex.org/C56435381","wikidata":"https://www.wikidata.org/wiki/Q1196371","display_name":"Geometric transformation","level":3,"score":0.41269999742507935},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.39480000734329224},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35989999771118164},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3571000099182129},{"id":"https://openalex.org/C32990609","wikidata":"https://www.wikidata.org/wiki/Q306542","display_name":"Transformation geometry","level":2,"score":0.3264000117778778},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.32499998807907104},{"id":"https://openalex.org/C104065381","wikidata":"https://www.wikidata.org/wiki/Q1002535","display_name":"Geometric modeling","level":2,"score":0.32179999351501465},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.3066999912261963},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.2863999903202057},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2831999957561493},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.28220000863075256},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.2621000111103058},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.25360000133514404},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.250900000333786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccma67641.2025.11369653","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccma67641.2025.11369653","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 13th International Conference on Control, Mechatronics and Automation (ICCMA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334111","display_name":"Innovation Fund","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1745334888","https://openalex.org/W2601564443","https://openalex.org/W2963870605","https://openalex.org/W3034421924","https://openalex.org/W3087425401","https://openalex.org/W3111221273","https://openalex.org/W3181848549","https://openalex.org/W4283814658","https://openalex.org/W4294982940","https://openalex.org/W4386076222","https://openalex.org/W4400859202","https://openalex.org/W4402727033","https://openalex.org/W4402754006","https://openalex.org/W4403887646","https://openalex.org/W4413465567"],"related_works":[],"abstract_inverted_index":{"Dental":[0],"burs":[1],"are":[2],"small,":[3],"elongated,":[4],"and":[5,11,32,82,111,131],"frequently":[6],"overlapping":[7],"components":[8],"whose":[9],"detection":[10,129],"counting":[12],"remain":[13],"a":[14,90,117],"major":[15],"obstacle":[16],"for":[17],"automated":[18],"inspection":[19],"systems":[20],"in":[21],"industrial":[22],"settings.":[23],"Conventional":[24],"visual":[25],"approaches":[26,139],"typically":[27],"suffer":[28],"from":[29],"low":[30],"precision":[31],"poor":[33],"robustness,":[34],"while":[35],"mainstream":[36],"deep":[37],"learning":[38],"detectors":[39],"fail":[40],"to":[41,43],"adapt":[42],"the":[44,70,80,97,101,124],"geometric":[45,67],"characteristics":[46],"of":[47,85,100],"such":[48],"slender,":[49],"orientation-varying":[50],"objects.":[51],"To":[52],"overcome":[53],"these":[54],"challenges,":[55],"this":[56],"paper":[57],"introduces":[58],"an":[59],"Direction-Adaptive":[60],"Convolution":[61],"(DAC)":[62],"mechanism":[63],"that":[64,123],"explicitly":[65],"integrates":[66],"priors":[68],"into":[69],"convolution":[71],"process.":[72],"A":[73],"compact":[74],"parameter":[75],"estimation":[76],"branch":[77],"dynamically":[78],"predicts":[79],"orientation":[81],"aspect":[83],"ratio":[84],"each":[86],"local":[87],"region,":[88],"generating":[89],"rotated":[91],"rectangular":[92],"receptive":[93],"field":[94],"aligned":[95],"with":[96,135],"principal":[98],"axis":[99],"object.":[102],"This":[103],"design":[104],"achieves":[105],"consistent":[106],"alignment":[107],"between":[108],"feature":[109],"sampling":[110],"object":[112],"geometry.":[113],"Comprehensive":[114],"experiments":[115],"on":[116],"newly":[118],"collected":[119],"dental-bur":[120],"dataset":[121],"verify":[122],"proposed":[125],"OAC":[126],"markedly":[127],"enhances":[128],"accuracy":[130],"computational":[132],"efficiency":[133],"compared":[134],"existing":[136],"adaptive":[137],"convolutional":[138]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-02-07T00:00:00"}
