{"id":"https://openalex.org/W4391128357","doi":"https://doi.org/10.1109/tii.2024.3353841","title":"Light-Weight Convolutional Neural Networks for Generative Robotic Grasping","display_name":"Light-Weight Convolutional Neural Networks for Generative Robotic Grasping","publication_year":2024,"publication_date":"2024-01-23","ids":{"openalex":"https://openalex.org/W4391128357","doi":"https://doi.org/10.1109/tii.2024.3353841"},"language":"en","primary_location":{"id":"doi:10.1109/tii.2024.3353841","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2024.3353841","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Industrial Informatics","raw_type":"journal-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/A5028781796","display_name":"Kui Fu","orcid":"https://orcid.org/0000-0001-7824-2454"},"institutions":[{"id":"https://openalex.org/I4210161599","display_name":"Hechi University","ror":"https://ror.org/05pjkyk24","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210161599"]},{"id":"https://openalex.org/I5343935","display_name":"Guilin University of Electronic Technology","ror":"https://ror.org/05arjae42","country_code":"CN","type":"education","lineage":["https://openalex.org/I5343935"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Kui Fu","raw_affiliation_strings":["School of Electronic and Automation, Guilin University of Electronic Technology, Guilin, China","School of Artificial Intelligence and Smart Manufacturing, Hechi University, Yizhou, China"],"raw_orcid":"https://orcid.org/0000-0001-7824-2454","affiliations":[{"raw_affiliation_string":"School of Electronic and Automation, Guilin University of Electronic Technology, Guilin, China","institution_ids":["https://openalex.org/I5343935"]},{"raw_affiliation_string":"School of Artificial Intelligence and Smart Manufacturing, Hechi University, Yizhou, China","institution_ids":["https://openalex.org/I4210161599"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051901649","display_name":"Xuanju Dang","orcid":"https://orcid.org/0000-0003-0626-689X"},"institutions":[{"id":"https://openalex.org/I5343935","display_name":"Guilin University of Electronic Technology","ror":"https://ror.org/05arjae42","country_code":"CN","type":"education","lineage":["https://openalex.org/I5343935"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuanju Dang","raw_affiliation_strings":["School of Electronic and Automation, Guilin University of Electronic Technology, Guilin, China"],"raw_orcid":"https://orcid.org/0000-0003-0626-689X","affiliations":[{"raw_affiliation_string":"School of Electronic and Automation, Guilin University of Electronic Technology, Guilin, China","institution_ids":["https://openalex.org/I5343935"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5028781796"],"corresponding_institution_ids":["https://openalex.org/I4210161599","https://openalex.org/I5343935"],"apc_list":null,"apc_paid":null,"fwci":8.6351,"has_fulltext":false,"cited_by_count":29,"citation_normalized_percentile":{"value":0.9826975,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"20","issue":"4","first_page":"6696","last_page":"6707"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9968000054359436,"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":0.9968000054359436,"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/T10571","display_name":"Robotic Mechanisms and Dynamics","score":0.9872999787330627,"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9650999903678894,"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":0.6680153608322144},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6510117053985596},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6000894904136658},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41206246614456177},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.38789162039756775}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6680153608322144},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6510117053985596},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6000894904136658},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41206246614456177},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38789162039756775}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tii.2024.3353841","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2024.3353841","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Industrial Informatics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2487135428","display_name":null,"funder_award_id":"2023GXNSFAA026025","funder_id":"https://openalex.org/F4320322768","funder_display_name":"Natural Science Foundation of Guangxi Province"},{"id":"https://openalex.org/G2503116900","display_name":null,"funder_award_id":"62263004","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322768","display_name":"Natural Science Foundation of Guangxi Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1892339738","https://openalex.org/W1999156278","https://openalex.org/W2067098972","https://openalex.org/W2123435073","https://openalex.org/W2140427427","https://openalex.org/W2302255633","https://openalex.org/W2476548250","https://openalex.org/W2565639579","https://openalex.org/W2600030077","https://openalex.org/W2808521881","https://openalex.org/W2921247092","https://openalex.org/W2953669419","https://openalex.org/W2962821282","https://openalex.org/W2962875890","https://openalex.org/W2963326767","https://openalex.org/W3007627128","https://openalex.org/W3013482323","https://openalex.org/W3047032303","https://openalex.org/W3056171435","https://openalex.org/W3081801393","https://openalex.org/W3104104643","https://openalex.org/W3130885760","https://openalex.org/W3170679572","https://openalex.org/W3179504572","https://openalex.org/W3186077919","https://openalex.org/W3217480528","https://openalex.org/W4205151370","https://openalex.org/W4205272422","https://openalex.org/W4206142116","https://openalex.org/W4210316419","https://openalex.org/W4226091687","https://openalex.org/W4226225308","https://openalex.org/W4226413077","https://openalex.org/W4289656330","https://openalex.org/W4292978855"],"related_works":["https://openalex.org/W2755342338","https://openalex.org/W2058170566","https://openalex.org/W2036807459","https://openalex.org/W2775347418","https://openalex.org/W1969923398","https://openalex.org/W2772917594","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2079911747"],"abstract_inverted_index":{"Grasp":[0],"planning":[1],"with":[2,134],"high-performance":[3],"and":[4,83,126,156,164],"efficiency":[5,128],"in":[6,161],"unstructured":[7],"environments":[8],"is":[9,35,46,71,92,107,171],"a":[10,28,66,75],"critical":[11],"problem":[12],"that":[13],"intelligent":[14],"robots":[15],"need":[16],"to":[17,20,37,49,73,94,109,140,181],"solve":[18,25],"urgently":[19],"complete":[21],"picking":[22],"tasks.":[23],"To":[24,79],"this":[26],"problem,":[27],"quantized":[29],"grasp":[30,52,68,77,97,103,113,122,151],"quality":[31,69],"generative":[32],"neural":[33,44],"network":[34,45,70],"proposed":[36,93,108],"generate":[38,50,74],"pixel-level":[39],"grasps.":[40],"A":[41],"light-weight":[42,64],"convolutional":[43],"first":[47],"used":[48],"initial":[51],"configurations.":[53,98],"Aiming":[54],"at":[55],"the":[56,63,81,86,96,111,116,120,127,144,148,169],"degradation":[57],"of":[58,85,124,129,154],"grasping":[59,145],"performance":[60],"caused":[61],"by":[62],"design,":[65],"decoupled":[67],"designed":[72],"pixel-wise":[76],"quality.":[78],"improve":[80],"robustness":[82],"generalization":[84],"model,":[87],"an":[88,100,174],"adaptive":[89],"filtering":[90],"method":[91,106],"filter":[95],"Then,":[99],"ellipse":[101],"fitting-based":[102],"pose":[104],"optimization":[105],"obtain":[110],"final":[112],"configuration.":[114],"On":[115],"public":[117],"Cornell":[118],"dataset,":[119],"state-of-the-art":[121],"accuracy":[123],"98.9%":[125],"15":[130],"ms":[131],"are":[132],"achieved,":[133],"approximately":[135],"564\u00d7":[136],"fewer":[137],"parameters":[138],"compared":[139],"comparable":[141],"performance.":[142],"In":[143],"experiments":[146],"on":[147,173],"robotic":[149],"platform,":[150],"success":[152],"rates":[153],"99%":[155],"93.4%":[157],"can":[158],"be":[159],"achieved":[160],"single":[162],"object":[163],"cluttered":[165],"scenes,":[166],"respectively.":[167],"Finally,":[168],"model":[170],"deployed":[172],"embedded":[175],"artificial":[176],"intelligence":[177],"(AI)":[178],"computing":[179],"device":[180],"verify":[182],"its":[183],"practicality.":[184]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":18},{"year":2024,"cited_by_count":6}],"updated_date":"2026-05-28T09:10:13.091523","created_date":"2025-10-10T00:00:00"}