{"id":"https://openalex.org/W4308236062","doi":"https://doi.org/10.1109/icip46576.2022.9897675","title":"Skip-MLP Network for Point Cloud Classification","display_name":"Skip-MLP Network for Point Cloud Classification","publication_year":2022,"publication_date":"2022-10-16","ids":{"openalex":"https://openalex.org/W4308236062","doi":"https://doi.org/10.1109/icip46576.2022.9897675"},"language":"en","primary_location":{"id":"doi:10.1109/icip46576.2022.9897675","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip46576.2022.9897675","pdf_url":null,"source":{"id":"https://openalex.org/S4363607719","display_name":"2022 IEEE International Conference on Image Processing (ICIP)","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":"2022 IEEE International Conference on Image Processing (ICIP)","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/A5106406674","display_name":"Zhichao Wang","orcid":"https://orcid.org/0009-0009-2624-8091"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhichao Wang","raw_affiliation_strings":["Xidian University,School of Microelectronics","School of Microelectronics, Xidian University"],"affiliations":[{"raw_affiliation_string":"Xidian University,School of Microelectronics","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Microelectronics, Xidian University","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072992909","display_name":"Qi Peng","orcid":"https://orcid.org/0000-0002-3520-8990"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Peng","raw_affiliation_strings":["Xidian University,School of Microelectronics","School of Microelectronics, Xidian University"],"affiliations":[{"raw_affiliation_string":"Xidian University,School of Microelectronics","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Microelectronics, Xidian University","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103271811","display_name":"Jie Li","orcid":"https://orcid.org/0000-0002-9769-8024"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Li","raw_affiliation_strings":["Xidian University,School of Microelectronics","School of Microelectronics, Xidian University"],"affiliations":[{"raw_affiliation_string":"Xidian University,School of Microelectronics","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Microelectronics, Xidian University","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5106406674"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":0.2062,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.55341506,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1001","last_page":"1005"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9975000023841858,"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/T11245","display_name":"Advanced Numerical Analysis Techniques","score":0.9925000071525574,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/encoding","display_name":"Encoding (memory)","score":0.7806580662727356},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7795718908309937},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.7239421010017395},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.7137705087661743},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.7112086415290833},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.559384286403656},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.5101945400238037},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5097836852073669},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4814559817314148},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.46160784363746643},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41748321056365967},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3878999948501587},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32952654361724854},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.2193910777568817},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10857275128364563}],"concepts":[{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.7806580662727356},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7795718908309937},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.7239421010017395},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.7137705087661743},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.7112086415290833},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.559384286403656},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.5101945400238037},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5097836852073669},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4814559817314148},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.46160784363746643},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41748321056365967},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3878999948501587},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32952654361724854},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2193910777568817},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10857275128364563},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"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/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","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},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip46576.2022.9897675","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip46576.2022.9897675","pdf_url":null,"source":{"id":"https://openalex.org/S4363607719","display_name":"2022 IEEE International Conference on Image Processing (ICIP)","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":"2022 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.7699999809265137}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1644641054","https://openalex.org/W2211722331","https://openalex.org/W2560609797","https://openalex.org/W2606202972","https://openalex.org/W2624503621","https://openalex.org/W2779385920","https://openalex.org/W2899663614","https://openalex.org/W2962731536","https://openalex.org/W2962928871","https://openalex.org/W2963053547","https://openalex.org/W2963094037","https://openalex.org/W2963121255","https://openalex.org/W2963158438","https://openalex.org/W2963719584","https://openalex.org/W2964239605","https://openalex.org/W2964253930","https://openalex.org/W2964342398","https://openalex.org/W2979750740","https://openalex.org/W3090670396","https://openalex.org/W3157424380","https://openalex.org/W3193895695","https://openalex.org/W6747324600","https://openalex.org/W6755977528"],"related_works":["https://openalex.org/W2357124094","https://openalex.org/W2387399993","https://openalex.org/W2389739210","https://openalex.org/W2348924972","https://openalex.org/W2365736347","https://openalex.org/W2595172197","https://openalex.org/W2047454415","https://openalex.org/W2070040999","https://openalex.org/W2387293848","https://openalex.org/W2250140200"],"abstract_inverted_index":{"The":[0],"encoding":[1,17,44,64,104],"method":[2,45],"for":[3,46,132],"local":[4,47,66],"neighborhood":[5,48],"of":[6,12,49,84,105,109],"sampling":[7,50,61,73,86,112],"points":[8,62,87,113],"is":[9,99,123],"the":[10,57,65,82,85,106,110,129],"bottleneck":[11],"point":[13,24,72,91,133],"cloud":[14,92,134],"learning.":[15],"Existing":[16],"methods":[18,131],"do":[19],"not":[20],"perform":[21,102],"well":[22],"on":[23,76,117],"clouds":[25],"with":[26,90],"low":[27],"density,":[28],"which":[29],"seriously":[30],"affects":[31],"its":[32],"application":[33],"in":[34,78],"real-world":[35],"scenarios.":[36],"In":[37],"this":[38],"paper,":[39],"we":[40],"propose":[41],"a":[42,71],"novel":[43],"points,":[51],"named":[52],"Skip-MLP.":[53],"It":[54],"can":[55],"establish":[56],"spatial":[58],"relationship":[59],"among":[60],"while":[63],"neighborhood.":[67],"We":[68],"simultaneously":[69],"adopt":[70],"scheme":[74],"based":[75],"learning,":[77],"order":[79],"to":[80,101],"enhance":[81],"adaptability":[83],"selection":[88],"strategy":[89],"density":[93],"changing.":[94],"Moreover,":[95],"an":[96],"attention":[97],"module":[98],"introduced":[100],"finegrained":[103],"key":[107],"features":[108],"embedded":[111],"neighborhoods.":[114],"Experimental":[115],"results":[116],"benchmarks":[118],"demonstrate":[119],"that":[120],"Skip-MLP":[121],"network":[122],"more":[124],"efficient":[125],"and":[126],"robust":[127],"than":[128],"previous":[130],"classification.":[135]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
