{"id":"https://openalex.org/W2569783404","doi":"https://doi.org/10.1109/cist.2016.7805096","title":"An automatic framework for 3D objects-parts learning","display_name":"An automatic framework for 3D objects-parts learning","publication_year":2016,"publication_date":"2016-10-01","ids":{"openalex":"https://openalex.org/W2569783404","doi":"https://doi.org/10.1109/cist.2016.7805096","mag":"2569783404"},"language":"en","primary_location":{"id":"doi:10.1109/cist.2016.7805096","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cist.2016.7805096","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 4th IEEE International Colloquium on Information Science and Technology (CiSt)","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/A5022443189","display_name":"Omar Herouane","orcid":null},"institutions":[{"id":"https://openalex.org/I4210145365","display_name":"Universit\u00e9 Hassan 1er","ror":"https://ror.org/03cdvht47","country_code":"MA","type":"education","lineage":["https://openalex.org/I4210145365"]}],"countries":["MA"],"is_corresponding":true,"raw_author_name":"Omar Herouane","raw_affiliation_strings":["Laboratory IIMSC, Univ. Hassan 1, Settat, Morocco"],"affiliations":[{"raw_affiliation_string":"Laboratory IIMSC, Univ. Hassan 1, Settat, Morocco","institution_ids":["https://openalex.org/I4210145365"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034303466","display_name":"Lahcen Moumoun","orcid":"https://orcid.org/0000-0003-3651-8699"},"institutions":[{"id":"https://openalex.org/I4210145365","display_name":"Universit\u00e9 Hassan 1er","ror":"https://ror.org/03cdvht47","country_code":"MA","type":"education","lineage":["https://openalex.org/I4210145365"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Lahcen Moumoun","raw_affiliation_strings":["Laboratory IIMSC, Univ. Hassan 1, Settat, Morocco"],"affiliations":[{"raw_affiliation_string":"Laboratory IIMSC, Univ. Hassan 1, Settat, Morocco","institution_ids":["https://openalex.org/I4210145365"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040232446","display_name":"Taoufiq Gadi","orcid":"https://orcid.org/0000-0002-2174-5816"},"institutions":[{"id":"https://openalex.org/I4210145365","display_name":"Universit\u00e9 Hassan 1er","ror":"https://ror.org/03cdvht47","country_code":"MA","type":"education","lineage":["https://openalex.org/I4210145365"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Taoufiq Gadi","raw_affiliation_strings":["Laboratory IIMSC, Univ. Hassan 1, Settat, Morocco"],"affiliations":[{"raw_affiliation_string":"Laboratory IIMSC, Univ. Hassan 1, Settat, Morocco","institution_ids":["https://openalex.org/I4210145365"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035441812","display_name":"Mohamed Chahhou","orcid":null},"institutions":[{"id":"https://openalex.org/I81605866","display_name":"Sidi Mohamed Ben Abdellah University","ror":"https://ror.org/04efg9a07","country_code":"MA","type":"education","lineage":["https://openalex.org/I81605866"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Mohamed Chahhou","raw_affiliation_strings":["Laboratory LIMS, Univ. Sidi Mohamed Ben Abdellah, Fes, Morocco"],"affiliations":[{"raw_affiliation_string":"Laboratory LIMS, Univ. Sidi Mohamed Ben Abdellah, Fes, Morocco","institution_ids":["https://openalex.org/I81605866"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5022443189"],"corresponding_institution_ids":["https://openalex.org/I4210145365"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15211405,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"7","issue":null,"first_page":"481","last_page":"486"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9993000030517578,"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":0.9993000030517578,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9980000257492065,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9973999857902527,"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/computer-science","display_name":"Computer science","score":0.8196526765823364},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.8014663457870483},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6817461848258972},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6612195372581482},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.64105224609375},{"id":"https://openalex.org/keywords/spectral-clustering","display_name":"Spectral clustering","score":0.5415213108062744},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.46128836274147034},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.42997556924819946},{"id":"https://openalex.org/keywords/market-segmentation","display_name":"Market segmentation","score":0.42571109533309937},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42442527413368225},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.417792409658432},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3636464476585388}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8196526765823364},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.8014663457870483},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6817461848258972},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6612195372581482},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.64105224609375},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.5415213108062744},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.46128836274147034},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.42997556924819946},{"id":"https://openalex.org/C125308379","wikidata":"https://www.wikidata.org/wiki/Q363057","display_name":"Market segmentation","level":2,"score":0.42571109533309937},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42442527413368225},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.417792409658432},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3636464476585388},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cist.2016.7805096","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cist.2016.7805096","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 4th IEEE International Colloquium on Information Science and Technology (CiSt)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1501418839","https://openalex.org/W1599356215","https://openalex.org/W1973414297","https://openalex.org/W1976638067","https://openalex.org/W1991337803","https://openalex.org/W2003067321","https://openalex.org/W2023808821","https://openalex.org/W2050204708","https://openalex.org/W2064058834","https://openalex.org/W2076374635","https://openalex.org/W2076633596","https://openalex.org/W2093717447","https://openalex.org/W2106723645","https://openalex.org/W2112076978","https://openalex.org/W2117824861","https://openalex.org/W2119823327","https://openalex.org/W2121947440","https://openalex.org/W2131686571","https://openalex.org/W2132914434","https://openalex.org/W2136595724","https://openalex.org/W2140055783","https://openalex.org/W2142663054","https://openalex.org/W2182827928","https://openalex.org/W3004732066","https://openalex.org/W6676769703","https://openalex.org/W6677416955","https://openalex.org/W6680240620","https://openalex.org/W6686104879"],"related_works":["https://openalex.org/W2592395359","https://openalex.org/W2045342254","https://openalex.org/W2535231171","https://openalex.org/W2142182663","https://openalex.org/W1501331687","https://openalex.org/W4255512592","https://openalex.org/W2501551404","https://openalex.org/W2326647871","https://openalex.org/W4205247302","https://openalex.org/W2468652214"],"abstract_inverted_index":{"3D":[0,19,46,80],"objects":[1,20,47],"learning":[2,26,94],"is":[3,31,70,107],"a":[4,32,42,52],"challenging":[5],"problem":[6],"in":[7],"computer":[8],"vision":[9],"and":[10,34,61,74,96],"digital":[11],"multimedia":[12],"due":[13],"to":[14,56,88,102],"the":[15,58,90,93,97,110],"wide":[16],"development":[17],"of":[18,72,79,92,99],"scanning":[21],"technology.":[22],"Nevertheless,":[23],"using":[24],"machine":[25],"for":[27,45,65],"solving":[28],"such":[29],"problems":[30],"potential":[33],"effective":[35],"tool.":[36],"In":[37],"this":[38],"paper,":[39],"we":[40],"propose":[41],"novel":[43],"approach":[44,69,95],"labeling,":[48],"it":[49],"relies":[50],"on":[51],"multi-class":[53],"boosting":[54],"algorithm":[55,64],"train":[57],"labeling":[59,75],"function":[60],"spectral":[62,100],"clustering":[63,101],"segmentation.":[66],"The":[67],"proposed":[68,111],"capable":[71],"segmenting":[73],"automatically":[76],"different":[77],"components":[78],"objects.":[81],"Experiments":[82],"are":[83],"divided":[84],"into":[85],"three":[86],"stages":[87],"test":[89],"efficiency":[91],"ability":[98],"give":[103],"semantic":[104],"segmentations.":[105],"It":[106],"shown":[108],"that":[109],"framework":[112],"achieves":[113],"better":[114],"performance.":[115]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
