{"id":"https://openalex.org/W2409171770","doi":"https://doi.org/10.1109/icra.2016.7487691","title":"Denoising auto-encoders for learning of objects and tools affordances in continuous space","display_name":"Denoising auto-encoders for learning of objects and tools affordances in continuous space","publication_year":2016,"publication_date":"2016-05-01","ids":{"openalex":"https://openalex.org/W2409171770","doi":"https://doi.org/10.1109/icra.2016.7487691","mag":"2409171770"},"language":"en","primary_location":{"id":"doi:10.1109/icra.2016.7487691","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2016.7487691","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5086561212","display_name":"Atabak Dehban","orcid":"https://orcid.org/0000-0002-4220-2247"},"institutions":[{"id":"https://openalex.org/I141596103","display_name":"University of Lisbon","ror":"https://ror.org/01c27hj86","country_code":"PT","type":"education","lineage":["https://openalex.org/I141596103"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Atabak Dehban","raw_affiliation_strings":["Institute for Systems and Robotics, Universidade de Lisboa, Lisbon, Portugal"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Systems and Robotics, Universidade de Lisboa, Lisbon, Portugal","institution_ids":["https://openalex.org/I141596103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064713691","display_name":"Lorenzo Jamone","orcid":"https://orcid.org/0000-0002-1521-6168"},"institutions":[{"id":"https://openalex.org/I141596103","display_name":"University of Lisbon","ror":"https://ror.org/01c27hj86","country_code":"PT","type":"education","lineage":["https://openalex.org/I141596103"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Lorenzo Jamone","raw_affiliation_strings":["Institute for Systems and Robotics, Universidade de Lisboa, Lisbon, Portugal"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Systems and Robotics, Universidade de Lisboa, Lisbon, Portugal","institution_ids":["https://openalex.org/I141596103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017354451","display_name":"Adam R. Kampff","orcid":"https://orcid.org/0000-0003-3079-019X"},"institutions":[{"id":"https://openalex.org/I2800011936","display_name":"Sainsbury Laboratory","ror":"https://ror.org/02tdtzx53","country_code":"GB","type":"facility","lineage":["https://openalex.org/I2800011936"]},{"id":"https://openalex.org/I4396570676","display_name":"Sainsbury Wellcome Centre","ror":"https://ror.org/04kjqkz56","country_code":"GB","type":"facility","lineage":["https://openalex.org/I124357947","https://openalex.org/I4396570676","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Adam R. Kampff","raw_affiliation_strings":["Champalimaud Neuroscience Programme, Sainsbury Welleome Centre for Neural Circuits and Behaviour (SWC), London, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Champalimaud Neuroscience Programme, Sainsbury Welleome Centre for Neural Circuits and Behaviour (SWC), London, UK","institution_ids":["https://openalex.org/I2800011936","https://openalex.org/I4396570676"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037378255","display_name":"Jos\u00e9 Santos-Victor","orcid":"https://orcid.org/0000-0002-9036-1728"},"institutions":[{"id":"https://openalex.org/I141596103","display_name":"University of Lisbon","ror":"https://ror.org/01c27hj86","country_code":"PT","type":"education","lineage":["https://openalex.org/I141596103"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Jose Santos-Victor","raw_affiliation_strings":["Institute for Systems and Robotics, Universidade de Lisboa, Lisbon, Portugal"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Systems and Robotics, Universidade de Lisboa, Lisbon, Portugal","institution_ids":["https://openalex.org/I141596103"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"19","issue":null,"first_page":"4866","last_page":"4871"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/affordance","display_name":"Affordance","score":0.8587433695793152},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7682812213897705},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6339107751846313},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.5470231771469116},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5116603374481201},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.48086196184158325},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.4691143333911896},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.4624972343444824},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.45963412523269653},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.43867436051368713},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4261585772037506},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.415862500667572}],"concepts":[{"id":"https://openalex.org/C194995250","wikidata":"https://www.wikidata.org/wiki/Q531136","display_name":"Affordance","level":2,"score":0.8587433695793152},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7682812213897705},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6339107751846313},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.5470231771469116},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5116603374481201},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.48086196184158325},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.4691143333911896},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.4624972343444824},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.45963412523269653},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.43867436051368713},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4261585772037506},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.415862500667572},{"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icra.2016.7487691","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2016.7487691","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},{"id":"pmh:oai:qmro.qmul.ac.uk:123456789/19470","is_oa":false,"landing_page_url":"http://qmro.qmul.ac.uk/xmlui/handle/123456789/19470","pdf_url":null,"source":{"id":"https://openalex.org/S4306400530","display_name":"Queen Mary Research Online (Queen Mary University of London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I166337079","host_organization_name":"Queen Mary University of London","host_organization_lineage":["https://openalex.org/I166337079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceeding"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.44999998807907104}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1933657216","https://openalex.org/W1964257831","https://openalex.org/W2004727380","https://openalex.org/W2019676146","https://openalex.org/W2023758701","https://openalex.org/W2025768430","https://openalex.org/W2029434782","https://openalex.org/W2041108426","https://openalex.org/W2082711337","https://openalex.org/W2088335308","https://openalex.org/W2101234009","https://openalex.org/W2111034658","https://openalex.org/W2132322793","https://openalex.org/W2134831918","https://openalex.org/W2144095552","https://openalex.org/W2146292423","https://openalex.org/W2146502635","https://openalex.org/W2152175008","https://openalex.org/W2154284891","https://openalex.org/W2155217025","https://openalex.org/W2161222115","https://openalex.org/W2184188583","https://openalex.org/W2321135324","https://openalex.org/W2484937297","https://openalex.org/W2914484425","https://openalex.org/W4255949318","https://openalex.org/W6681034127","https://openalex.org/W6681435938","https://openalex.org/W6686207219"],"related_works":["https://openalex.org/W73545470","https://openalex.org/W4224266612","https://openalex.org/W2383394264","https://openalex.org/W4320153225","https://openalex.org/W4293261942","https://openalex.org/W3125968744","https://openalex.org/W203959209","https://openalex.org/W2167701463","https://openalex.org/W2110287964","https://openalex.org/W4307407935"],"abstract_inverted_index":{"The":[0,77],"concept":[1],"of":[2,7,32,65,73,156,175,197],"affordances":[3,64],"facilitates":[4],"the":[5,18,63,71,114,128,154,157,165,187],"encoding":[6],"relations":[8],"between":[9],"actions":[10],"and":[11,30,37,60,67,88,130,177],"effects":[12],"in":[13,118,133,142,169,193],"an":[14,21,54,90],"environment":[15,59],"centered":[16],"around":[17],"agent.":[19],"Such":[20],"interpretation":[22],"has":[23,107],"important":[24],"impacts":[25],"on":[26,46,75],"several":[27],"cognitive":[28],"capabilities":[29],"manifestations":[31],"intelligence,":[33],"such":[34],"as":[35,80],"prediction":[36],"planning.":[38],"In":[39],"this":[40],"paper,":[41],"a":[42,81,95,98,194],"new":[43,188],"framework":[44,83],"based":[45],"denoising":[47],"Auto-encoders":[48],"(dA)":[49],"is":[50,116,146],"proposed":[51],"which":[52,143],"allows":[53],"agent":[55],"to":[56,84,126,140],"explore":[57],"its":[58],"actively":[61],"learn":[62],"objects":[66],"tools":[68],"by":[69,152],"observing":[70],"consequences":[72],"acting":[74],"them.":[76],"dA":[78,115],"serves":[79],"unified":[82],"fuse":[85],"multi-modal":[86],"data":[87,144],"retrieve":[89],"entire":[91],"missing":[92],"modality":[93,99],"or":[94],"feature":[96],"within":[97],"given":[100],"information":[101],"about":[102],"other":[103],"modalities.":[104],"This":[105],"work":[106],"two":[108],"major":[109],"contributions.":[110],"First,":[111],"since":[112],"training":[113],"done":[117],"continuous":[119],"space,":[120],"there":[121],"will":[122],"be":[123,136,161,191],"no":[124],"need":[125],"discretize":[127],"dataset":[129],"higher":[131],"accuracies":[132],"inference":[134],"can":[135,160,190],"achieved":[137],"with":[138],"respect":[139],"approaches":[141,185],"discretization":[145],"required":[147],"(e.g.":[148],"Bayesian":[149],"networks).":[150],"Second,":[151],"fixing":[153],"structure":[155],"dA,":[158],"knowledge":[159],"added":[162],"incrementally":[163],"making":[164],"architecture":[166],"particularly":[167],"useful":[168],"online":[170],"learning":[171],"scenarios.":[172],"Evaluation":[173],"scores":[174],"real":[176],"simulated":[178],"robotic":[179],"experiments":[180],"show":[181],"improvements":[182],"over":[183],"previous":[184],"while":[186],"model":[189],"applied":[192],"wider":[195],"range":[196],"domains.":[198]},"counts_by_year":[{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":8},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
