{"id":"https://openalex.org/W4385484713","doi":"https://doi.org/10.1109/ijcnn54540.2023.10191465","title":"Object View Prediction with Aleatoric Uncertainty for Robotic Grasping","display_name":"Object View Prediction with Aleatoric Uncertainty for Robotic Grasping","publication_year":2023,"publication_date":"2023-06-18","ids":{"openalex":"https://openalex.org/W4385484713","doi":"https://doi.org/10.1109/ijcnn54540.2023.10191465"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn54540.2023.10191465","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn54540.2023.10191465","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Joint Conference on Neural Networks (IJCNN)","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/A5068755328","display_name":"Constanze Schwan","orcid":"https://orcid.org/0000-0001-8976-7766"},"institutions":[{"id":"https://openalex.org/I20121455","display_name":"Bielefeld University","ror":"https://ror.org/02hpadn98","country_code":"DE","type":"education","lineage":["https://openalex.org/I20121455"]},{"id":"https://openalex.org/I203082224","display_name":"Hochschule Bielefeld","ror":"https://ror.org/00edvg943","country_code":"DE","type":"education","lineage":["https://openalex.org/I203082224"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Constanze Schwan","raw_affiliation_strings":["Bielefeld University of Applied Sciences and Arts,Faculty of Engineering and Mathematics,Bielefeld,Germany","Faculty of Engineering and Mathematics, Bielefeld University of Applied Sciences and Arts, Bielefeld, Germany"],"affiliations":[{"raw_affiliation_string":"Bielefeld University of Applied Sciences and Arts,Faculty of Engineering and Mathematics,Bielefeld,Germany","institution_ids":["https://openalex.org/I203082224","https://openalex.org/I20121455"]},{"raw_affiliation_string":"Faculty of Engineering and Mathematics, Bielefeld University of Applied Sciences and Arts, Bielefeld, Germany","institution_ids":["https://openalex.org/I203082224"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051039216","display_name":"Wolfram Schenck","orcid":"https://orcid.org/0000-0003-3300-2048"},"institutions":[{"id":"https://openalex.org/I20121455","display_name":"Bielefeld University","ror":"https://ror.org/02hpadn98","country_code":"DE","type":"education","lineage":["https://openalex.org/I20121455"]},{"id":"https://openalex.org/I203082224","display_name":"Hochschule Bielefeld","ror":"https://ror.org/00edvg943","country_code":"DE","type":"education","lineage":["https://openalex.org/I203082224"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Wolfram Schenck","raw_affiliation_strings":["Bielefeld University of Applied Sciences and Arts,Faculty of Engineering and Mathematics,Bielefeld,Germany","Faculty of Engineering and Mathematics, Bielefeld University of Applied Sciences and Arts, Bielefeld, Germany"],"affiliations":[{"raw_affiliation_string":"Bielefeld University of Applied Sciences and Arts,Faculty of Engineering and Mathematics,Bielefeld,Germany","institution_ids":["https://openalex.org/I203082224","https://openalex.org/I20121455"]},{"raw_affiliation_string":"Faculty of Engineering and Mathematics, Bielefeld University of Applied Sciences and Arts, Bielefeld, Germany","institution_ids":["https://openalex.org/I203082224"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5068755328"],"corresponding_institution_ids":["https://openalex.org/I20121455","https://openalex.org/I203082224"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10129138,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"110","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"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/T10653","display_name":"Robot Manipulation and Learning","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9909999966621399,"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/grasp","display_name":"GRASP","score":0.7291603684425354},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7149482369422913},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6680047512054443},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5780683755874634},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.5722405314445496},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.5379320979118347},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4829656183719635},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.4762941896915436},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.46959224343299866},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.46606379747390747},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.45392367243766785},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.4315231442451477},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.4200955927371979},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35502007603645325},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3462245762348175},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2158946394920349},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.12492135167121887},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1157580018043518}],"concepts":[{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.7291603684425354},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7149482369422913},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6680047512054443},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5780683755874634},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.5722405314445496},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.5379320979118347},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4829656183719635},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.4762941896915436},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.46959224343299866},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.46606379747390747},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.45392367243766785},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.4315231442451477},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.4200955927371979},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35502007603645325},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3462245762348175},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2158946394920349},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12492135167121887},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1157580018043518},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn54540.2023.10191465","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn54540.2023.10191465","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4708818502","display_name":null,"funder_award_id":"34.EFRE-0300119,34.EFRE-0300180","funder_id":"https://openalex.org/F4320335322","funder_display_name":"European Regional Development Fund"}],"funders":[{"id":"https://openalex.org/F4320335322","display_name":"European Regional Development Fund","ror":"https://ror.org/00k4n6c32"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1572975105","https://openalex.org/W1706124764","https://openalex.org/W2082511574","https://openalex.org/W2111959010","https://openalex.org/W2156583822","https://openalex.org/W2524140598","https://openalex.org/W2600383743","https://openalex.org/W2787283669","https://openalex.org/W2886499109","https://openalex.org/W2887976372","https://openalex.org/W2910474428","https://openalex.org/W2963033241","https://openalex.org/W2975039016","https://openalex.org/W3003477985","https://openalex.org/W3013643479","https://openalex.org/W3032127812","https://openalex.org/W3039645397","https://openalex.org/W3056171435","https://openalex.org/W3087305890","https://openalex.org/W3090032229","https://openalex.org/W3104104643","https://openalex.org/W3119044505","https://openalex.org/W3131115577","https://openalex.org/W3134774296","https://openalex.org/W3185930823","https://openalex.org/W3200932651","https://openalex.org/W4221157442","https://openalex.org/W4221167377","https://openalex.org/W4312960604","https://openalex.org/W4394671432","https://openalex.org/W6687484953","https://openalex.org/W6748369306","https://openalex.org/W6754345201","https://openalex.org/W6783565680","https://openalex.org/W6799088282"],"related_works":["https://openalex.org/W2163296013","https://openalex.org/W2743859443","https://openalex.org/W2326995835","https://openalex.org/W165915117","https://openalex.org/W2059402478","https://openalex.org/W2123347777","https://openalex.org/W4387804363","https://openalex.org/W2019547100","https://openalex.org/W2477150073","https://openalex.org/W2515493494"],"abstract_inverted_index":{"In":[0,45],"vision-based":[1],"robotic":[2],"grasping":[3],"the":[4,15,25,28,36,74,83,86,91,97,111,121,127,135],"prediction":[5,38],"of":[6,14,39,60,85],"grasps":[7],"is":[8,33,43],"made":[9],"on":[10],"an":[11,61],"RGB-D":[12],"image":[13,67],"scene":[16],"from":[17,63],"a":[18,40,50,64,104,132],"pre-grasp":[19],"position.":[20],"Due":[21],"to":[22,30,81,103],"perspective":[23],"occlusions":[24],"information":[26],"about":[27],"object":[29,62,88,106],"be":[31,79],"grasped":[32],"incomplete.":[34],"Therefore":[35],"reliable":[37],"successful":[41],"grasp":[42],"difficult.":[44],"this":[46],"study":[47],"we":[48,109,130],"investigate":[49,110],"convolutional":[51],"neural":[52],"network":[53],"that":[54],"can":[55,78],"predict":[56,82],"several":[57],"depth":[58,66],"views":[59],"single":[65],"and":[68,120],"camera":[69],"movements.":[70],"We":[71],"show":[72],"how":[73],"heteroscedastic":[75],"aleatoric":[76,98],"uncertainty":[77,84,99,129,136],"used":[80],"generated":[87],"views.":[89],"As":[90],"classical":[92],"Negative-Log-Likelihood":[93],"loss":[94,118],"function":[95,119],"for":[96],"does":[100],"not":[101],"converge":[102],"meaningful":[105],"view":[107],"prediction,":[108],"modified":[112],"<tex":[113],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[114],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\beta-":[115],"\\mathbf{Negative}$</tex>":[116],"-Log-Likelihood":[117],"Moment":[122],"Matching":[123],"loss.":[124],"For":[125],"assessing":[126],"predicted":[128],"introduce":[131],"new":[133],"measure,":[134],"weighted":[137],"intersection":[138],"over":[139],"union":[140],"value.":[141]},"counts_by_year":[],"updated_date":"2025-12-23T23:11:35.936235","created_date":"2025-10-10T00:00:00"}
