{"id":"https://openalex.org/W2963326767","doi":"https://doi.org/10.1109/iros.2017.8202237","title":"Robotic grasp detection using deep convolutional neural networks","display_name":"Robotic grasp detection using deep convolutional neural networks","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2963326767","doi":"https://doi.org/10.1109/iros.2017.8202237","mag":"2963326767"},"language":"en","primary_location":{"id":"doi:10.1109/iros.2017.8202237","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2017.8202237","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","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/A5031476331","display_name":"Sulabh Kumra","orcid":"https://orcid.org/0000-0003-2792-0969"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]},{"id":"https://openalex.org/I173498003","display_name":"Palo Alto Research Center","ror":"https://ror.org/0529fxt39","country_code":"US","type":"facility","lineage":["https://openalex.org/I173498003","https://openalex.org/I4210132870"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Sulabh Kumra","raw_affiliation_strings":["Department of Electrical Engineering, Rochester Institute of Technology, Rochester, NY, USA","Xerox Corporation, Webster, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Rochester Institute of Technology, Rochester, NY, USA","institution_ids":["https://openalex.org/I155173764"]},{"raw_affiliation_string":"Xerox Corporation, Webster, NY, USA","institution_ids":["https://openalex.org/I173498003"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046979072","display_name":"Christopher Kanan","orcid":"https://orcid.org/0000-0002-6412-995X"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christopher Kanan","raw_affiliation_strings":["Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY, USA"],"affiliations":[{"raw_affiliation_string":"Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY, USA","institution_ids":["https://openalex.org/I155173764"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5031476331"],"corresponding_institution_ids":["https://openalex.org/I155173764","https://openalex.org/I173498003"],"apc_list":null,"apc_paid":null,"fwci":33.634,"has_fulltext":false,"cited_by_count":536,"citation_normalized_percentile":{"value":0.99907957,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"769","last_page":"776"},"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":0.9918000102043152,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.989799976348877,"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":0.9594746828079224},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8716626167297363},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8545370101928711},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7898654937744141},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7697779536247253},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6500145792961121},{"id":"https://openalex.org/keywords/robotics","display_name":"Robotics","score":0.6178423166275024},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5965419411659241},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4653208255767822},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.45946502685546875},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.4567708671092987},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.2822018265724182}],"concepts":[{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.9594746828079224},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8716626167297363},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8545370101928711},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7898654937744141},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7697779536247253},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6500145792961121},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.6178423166275024},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5965419411659241},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4653208255767822},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.45946502685546875},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.4567708671092987},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2822018265724182},{"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/iros.2017.8202237","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2017.8202237","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.6299999952316284}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W70651934","https://openalex.org/W301022506","https://openalex.org/W1526127063","https://openalex.org/W1593727536","https://openalex.org/W1892339738","https://openalex.org/W1999156278","https://openalex.org/W2033223309","https://openalex.org/W2041376653","https://openalex.org/W2047346158","https://openalex.org/W2059625476","https://openalex.org/W2072242701","https://openalex.org/W2089630413","https://openalex.org/W2101024363","https://openalex.org/W2103305545","https://openalex.org/W2108598243","https://openalex.org/W2117539524","https://openalex.org/W2119112357","https://openalex.org/W2123435073","https://openalex.org/W2130942839","https://openalex.org/W2145287260","https://openalex.org/W2149933564","https://openalex.org/W2157331557","https://openalex.org/W2163605009","https://openalex.org/W2165603175","https://openalex.org/W2194775991","https://openalex.org/W2201912979","https://openalex.org/W2414685554","https://openalex.org/W2443711627","https://openalex.org/W2485911221","https://openalex.org/W2523315006","https://openalex.org/W2572996265","https://openalex.org/W2919115771","https://openalex.org/W2962724911","https://openalex.org/W2962736495","https://openalex.org/W2963654160","https://openalex.org/W2964161785","https://openalex.org/W4239072543","https://openalex.org/W4299518610","https://openalex.org/W6675525543","https://openalex.org/W6676297131","https://openalex.org/W6679436768","https://openalex.org/W6682132143","https://openalex.org/W6684191040","https://openalex.org/W6697071109"],"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/W2969228573","https://openalex.org/W2963690996"],"abstract_inverted_index":{"Deep":[0],"learning":[1],"has":[2,23],"significantly":[3],"advanced":[4],"computer":[5],"vision":[6],"and":[7,75,107],"natural":[8],"language":[9],"processing.":[10],"While":[11],"there":[12],"have":[13],"been":[14,25],"some":[15],"successes":[16],"in":[17],"robotics":[18],"using":[19,53],"deep":[20,65],"learning,":[21],"it":[22],"not":[24],"widely":[26],"adopted.":[27],"In":[28],"this":[29],"paper,":[30],"we":[31],"present":[32],"a":[33,46,64,78],"novel":[34,51],"robotic":[35,48,117],"grasp":[36,86,118],"detection":[37],"system":[38],"that":[39],"predicts":[40],"the":[41,54,58,73,85,89,102,114],"best":[42],"grasping":[43],"pose":[44],"of":[45,57,91,99],"parallel-plate":[47],"gripper":[49],"for":[50,88,116],"objects":[52],"RGB-D":[55],"image":[56],"scene.":[59],"The":[60],"proposed":[61],"model":[62,95],"uses":[63,77],"convolutional":[66,80],"neural":[67,81],"network":[68,82],"to":[69,83],"extract":[70],"features":[71],"from":[72],"scene":[74],"then":[76],"shallow":[79],"predict":[84],"configuration":[87],"object":[90],"interest.":[92],"Our":[93],"multi-modal":[94],"achieved":[96],"an":[97],"accuracy":[98],"89.21%":[100],"on":[101],"standard":[103],"Cornell":[104],"Grasp":[105],"Dataset":[106],"runs":[108],"at":[109],"real-time":[110],"speeds.":[111],"This":[112],"redefines":[113],"state-of-the-art":[115],"detection.":[119]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":45},{"year":2024,"cited_by_count":70},{"year":2023,"cited_by_count":80},{"year":2022,"cited_by_count":84},{"year":2021,"cited_by_count":88},{"year":2020,"cited_by_count":86},{"year":2019,"cited_by_count":51},{"year":2018,"cited_by_count":25},{"year":2017,"cited_by_count":3}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
