{"id":"https://openalex.org/W4366380948","doi":"https://doi.org/10.1145/3584376.3584539","title":"A fast and accurate point cloud registration network for industrial point cloud data","display_name":"A fast and accurate point cloud registration network for industrial point cloud data","publication_year":2022,"publication_date":"2022-12-16","ids":{"openalex":"https://openalex.org/W4366380948","doi":"https://doi.org/10.1145/3584376.3584539"},"language":"en","primary_location":{"id":"doi:10.1145/3584376.3584539","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3584376.3584539","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 4th International Conference on Robotics, Intelligent Control and Artificial Intelligence","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/A5018778473","display_name":"Quan Zhong","orcid":"https://orcid.org/0000-0001-5719-4289"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Quan Zhong","raw_affiliation_strings":["Anhui University, China"],"raw_orcid":"https://orcid.org/0000-0001-5719-4289","affiliations":[{"raw_affiliation_string":"Anhui University, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046171312","display_name":"Hua-Feng Dai","orcid":"https://orcid.org/0000-0001-7323-4842"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huafeng Dai","raw_affiliation_strings":["Tsinghua University, China"],"raw_orcid":"https://orcid.org/0000-0001-7323-4842","affiliations":[{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059623751","display_name":"Jun Shao","orcid":"https://orcid.org/0000-0003-0411-2491"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jun Shao","raw_affiliation_strings":["LCFC (Hefei) Electronics Technology Co., Ltd., China"],"raw_orcid":"https://orcid.org/0000-0003-0411-2491","affiliations":[{"raw_affiliation_string":"LCFC (Hefei) Electronics Technology Co., Ltd., China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064597384","display_name":"Jyun-Rong Wang","orcid":"https://orcid.org/0000-0003-0438-2192"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jyunrong Wang","raw_affiliation_strings":["Hefei University of Technology, China"],"raw_orcid":"https://orcid.org/0000-0003-0438-2192","affiliations":[{"raw_affiliation_string":"Hefei University of Technology, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042714880","display_name":"Taogen Chen","orcid":"https://orcid.org/0000-0002-1013-5051"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Taogen Chen","raw_affiliation_strings":["LCFC (Hefei) Electronics Technology Co., Ltd., China"],"raw_orcid":"https://orcid.org/0000-0002-1013-5051","affiliations":[{"raw_affiliation_string":"LCFC (Hefei) Electronics Technology Co., Ltd., China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063746958","display_name":"Hao Liu","orcid":"https://orcid.org/0000-0003-1445-4073"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hao Liu","raw_affiliation_strings":["LCFC (Hefei) Electronics Technology Co., Ltd., China"],"raw_orcid":"https://orcid.org/0000-0003-1445-4073","affiliations":[{"raw_affiliation_string":"LCFC (Hefei) Electronics Technology Co., Ltd., China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"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":0.32418699,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"913","last_page":"918"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9969000220298767,"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"}},{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental 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":0.7979811429977417},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.7634897828102112},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.5990041494369507},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5281187295913696},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5154879689216614},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.48551249504089355},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.47409185767173767},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43318772315979004},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4299834966659546},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09917405247688293}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7979811429977417},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.7634897828102112},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.5990041494369507},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5281187295913696},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5154879689216614},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.48551249504089355},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.47409185767173767},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43318772315979004},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4299834966659546},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09917405247688293},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3584376.3584539","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3584376.3584539","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 4th International Conference on Robotics, Intelligent Control and Artificial Intelligence","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":0.6299999952316284}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1984905474","https://openalex.org/W2037686083","https://openalex.org/W2049981393","https://openalex.org/W2053994417","https://openalex.org/W2063549868","https://openalex.org/W2115579991","https://openalex.org/W2119851068","https://openalex.org/W2160821342","https://openalex.org/W2161168419","https://openalex.org/W2252822738","https://openalex.org/W2344109021","https://openalex.org/W2566265240","https://openalex.org/W2624503621","https://openalex.org/W2768625376","https://openalex.org/W2908238389","https://openalex.org/W2950642167","https://openalex.org/W3021015133","https://openalex.org/W4221149978","https://openalex.org/W4249866455","https://openalex.org/W6640300118","https://openalex.org/W6761544809","https://openalex.org/W6761706501","https://openalex.org/W6770795054","https://openalex.org/W6775979993"],"related_works":["https://openalex.org/W4244478748","https://openalex.org/W4223488648","https://openalex.org/W2134969820","https://openalex.org/W2251605416","https://openalex.org/W4389340727","https://openalex.org/W4205786897","https://openalex.org/W3150465815","https://openalex.org/W1997222214","https://openalex.org/W2802581102","https://openalex.org/W2070395303"],"abstract_inverted_index":{"The":[0,86],"point":[1,24,41,80,111],"cloud":[2,25,81,112],"registration":[3,82,113,155],"task":[4,83],"for":[5,58],"anomaly":[6],"detection":[7],"in":[8,38,84,122,125,129,135,166],"industry":[9,65],"has":[10,28],"the":[11,22,29,63,79,104,110,118,148,154,160,163,167,177,180],"requirements":[12],"of":[13,31,36,99],"minimal":[14],"inference":[15,136],"time":[16],"and":[17,43,75,88,107,132,157],"maximal":[18],"performance":[19,156],"by":[20,48],"using":[21],"industrial":[23],"data":[26],"which":[27,138],"characteristics":[30],"high":[32],"precision,":[33],"large":[34],"number":[35],"points":[37],"a":[39,55,69,97,116],"single":[40],"cloud,":[42],"easy":[44],"to":[45,73,77,94,102,108],"be":[46,172],"affected":[47],"noise.":[49],"In":[50],"this":[51],"work,":[52],"we":[53],"curated":[54],"laptop":[56],"dataset":[57,161],"testing":[59],"our":[60],"network":[61],"on":[62,159],"real":[64,164],"situation.":[66],"We":[67],"propose":[68],"sampling-registration":[70,142],"combination,":[71],"SampleNet-iPCRNet,":[72],"fast":[74],"accurate":[76],"perform":[78,109],"industry.":[85,168],"SampleNet":[87],"an":[89],"iterative":[90],"PCRNet":[91],"are":[92],"cooperated":[93],"simultaneously":[95],"sample":[96],"set":[98],"representative":[100],"data,":[101],"enhance":[103],"noise":[105],"resistance,":[106],"task.":[114],"As":[115],"result,":[117],"SampleNet-iPCRNet":[119],"achieves":[120],"0.9849":[121],"AUC,":[123],"4.1054":[124],"rotation":[126],"error,":[127,131],"0.0021":[128],"translation":[130],"182":[133],"ms":[134],"speed":[137,158],"outperforming":[139],"among":[140],"other":[141],"combination":[143],"strategies.":[144],"Results":[145],"show":[146],"that":[147],"proposed":[149],"method":[150],"can":[151,171],"effectively":[152],"improve":[153],"representing":[162],"situation":[165],"Supplementary":[169],"information":[170],"available":[173],"at:":[174],"https://pan.baidu.com/s/1CwqSb_oMRrdN5x3ipAYfuQ":[175],"with":[176],"jb0y":[178],"as":[179],"extraction":[181],"code.":[182]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}