{"id":"https://openalex.org/W3168931735","doi":"https://doi.org/10.1109/iccicc50026.2020.9450222","title":"Local Learning in Point Clouds based on Spectral Pooling","display_name":"Local Learning in Point Clouds based on Spectral Pooling","publication_year":2020,"publication_date":"2020-09-26","ids":{"openalex":"https://openalex.org/W3168931735","doi":"https://doi.org/10.1109/iccicc50026.2020.9450222","mag":"3168931735"},"language":"en","primary_location":{"id":"doi:10.1109/iccicc50026.2020.9450222","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccicc50026.2020.9450222","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 19th International Conference on Cognitive Informatics &amp; Cognitive Computing (ICCI*CC)","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/A5091351580","display_name":"Yushi Li","orcid":"https://orcid.org/0000-0001-7164-5605"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Yushi Li","raw_affiliation_strings":["Department of Computing, The Hong Kong Polytechnic University"],"affiliations":[{"raw_affiliation_string":"Department of Computing, The Hong Kong Polytechnic University","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002562865","display_name":"George Baciu","orcid":"https://orcid.org/0000-0002-1766-6357"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"George Baciu","raw_affiliation_strings":["Department of Computing, The Hong Kong Polytechnic University"],"affiliations":[{"raw_affiliation_string":"Department of Computing, The Hong Kong Polytechnic University","institution_ids":["https://openalex.org/I14243506"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5091351580"],"corresponding_institution_ids":["https://openalex.org/I14243506"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.24115632,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":null,"first_page":"84","last_page":"91"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9991999864578247,"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":0.9959999918937683,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.8660110831260681},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7621052265167236},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6238713264465332},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.5549418330192566},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5328937768936157},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5247737765312195},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5012004375457764},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.49664026498794556},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.47033414244651794},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44975537061691284},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.41850218176841736},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09382125735282898}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.8660110831260681},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7621052265167236},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6238713264465332},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.5549418330192566},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5328937768936157},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5247737765312195},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5012004375457764},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.49664026498794556},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.47033414244651794},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44975537061691284},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.41850218176841736},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09382125735282898},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccicc50026.2020.9450222","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccicc50026.2020.9450222","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 19th International Conference on Cognitive Informatics &amp; Cognitive Computing (ICCI*CC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.4099999964237213,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W1563354748","https://openalex.org/W1564871316","https://openalex.org/W1735588541","https://openalex.org/W1772650917","https://openalex.org/W1920022804","https://openalex.org/W1929856797","https://openalex.org/W1955055330","https://openalex.org/W1983670955","https://openalex.org/W1989625560","https://openalex.org/W2059917035","https://openalex.org/W2107235635","https://openalex.org/W2116032541","https://openalex.org/W2130558599","https://openalex.org/W2160821342","https://openalex.org/W2161860896","https://openalex.org/W2162149523","https://openalex.org/W2211722331","https://openalex.org/W2398467116","https://openalex.org/W2560609797","https://openalex.org/W2606202972","https://openalex.org/W2766448241","https://openalex.org/W2779385920","https://openalex.org/W2889300857","https://openalex.org/W2902302021","https://openalex.org/W2962731536","https://openalex.org/W2963017945","https://openalex.org/W2963021451","https://openalex.org/W2963121255","https://openalex.org/W2963425704","https://openalex.org/W2963502507","https://openalex.org/W2963666542","https://openalex.org/W2963830382","https://openalex.org/W2964321699","https://openalex.org/W2979750740","https://openalex.org/W3101921002","https://openalex.org/W3102669005","https://openalex.org/W6634014874","https://openalex.org/W6637923771","https://openalex.org/W6638039622","https://openalex.org/W6640083356","https://openalex.org/W6640300118","https://openalex.org/W6720006811","https://openalex.org/W6739778489","https://openalex.org/W6747324600","https://openalex.org/W6747904511","https://openalex.org/W6747954111","https://openalex.org/W6749116069","https://openalex.org/W6754789060","https://openalex.org/W6763422710"],"related_works":["https://openalex.org/W2953234277","https://openalex.org/W2626256601","https://openalex.org/W147410782","https://openalex.org/W2900413183","https://openalex.org/W4390975304","https://openalex.org/W3022252430","https://openalex.org/W4287804464","https://openalex.org/W3048601286","https://openalex.org/W2965925734","https://openalex.org/W4309346246"],"abstract_inverted_index":{"As":[0],"one":[1],"of":[2,12,38,74,92,130,189],"the":[3,10,26,35,72,83,88],"most":[4,43],"fundamental":[5],"geometric":[6,160],"data":[7,90,161],"types":[8],"for":[9,66],"representation":[11],"space":[13],"and":[14,31,62,112,133,148,180,195],"object":[15],"shapes,":[16],"a":[17,50,117,142,170],"point":[18,39,85,144,172,185,199],"cloud":[19,145,200],"usually":[20],"maintains":[21],"much":[22],"structural":[23],"information":[24],"about":[25],"spatial":[27],"relationship":[28],"between":[29],"objects":[30],"their":[32],"features.":[33],"However,":[34,136],"relative":[36],"sparseness":[37],"clouds":[40,86],"sampled":[41],"in":[42,116,127,138,183],"practical":[44],"applications":[45],"make":[46],"extracting":[47],"information-rich":[48],"features":[49,111,182],"major":[51],"challenge.":[52],"Traditionally,":[53],"feature":[54,60,106],"extraction":[55],"algorithms":[56],"resorted":[57],"to":[58,81,156,168,178],"structured":[59],"engineering":[61,107],"used":[63],"handcrafted":[64],"representations":[65],"some":[67],"specific":[68],"problems.":[69],"Motivated":[70],"by":[71],"development":[73],"deep":[75,100],"neural":[76],"networks,":[77],"many":[78],"researchers":[79],"started":[80],"handle":[82],"unstructured":[84],"from":[87],"raw":[89],"samples":[91],"3D":[93,143,159,184],"scanning":[94],"devices.":[95],"Some":[96],"important":[97],"advantages":[98],"that":[99],"learning":[101,121],"frameworks":[102,153],"have":[103,123],"over":[104],"traditional":[105,151],"is":[108,146],"generalizing":[109],"complex":[110],"associated":[113],"semantic":[114],"concepts":[115],"hierarchical":[118],"manner.":[119],"Deep":[120],"models":[122],"achieved":[124],"significant":[125],"landmarks":[126],"cognitive":[128],"processing":[129],"speech,":[131],"image,":[132],"video":[134],"signals.":[135],"unlike":[137],"2D":[139],"image":[140],"processing,":[141],"irregular":[147],"sparse.":[149],"Hence,":[150],"network":[152,174],"are":[154,192],"difficult":[155],"apply":[157],"on":[158,198],"directly.":[162],"In":[163],"this":[164],"paper,":[165],"we":[166],"propose":[167],"integrate":[169],"local":[171],"convolution":[173],"with":[175],"spectral":[176],"pooling":[177],"aggregate":[179],"learn":[181],"clouds.":[186],"The":[187],"benefits":[188],"our":[190],"framework":[191],"fast":[193],"convergence":[194],"competitive":[196],"performance":[197],"classification.":[201]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
