{"id":"https://openalex.org/W4386159091","doi":"https://doi.org/10.1109/icarm58088.2023.10218848","title":"A Proposed Grasp Detection Based on Improved Dense Convolutional Neural Networks","display_name":"A Proposed Grasp Detection Based on Improved Dense Convolutional Neural Networks","publication_year":2023,"publication_date":"2023-07-08","ids":{"openalex":"https://openalex.org/W4386159091","doi":"https://doi.org/10.1109/icarm58088.2023.10218848"},"language":"en","primary_location":{"id":"doi:10.1109/icarm58088.2023.10218848","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icarm58088.2023.10218848","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Conference on Advanced Robotics and Mechatronics (ICARM)","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/A5066561534","display_name":"Tianya You","orcid":"https://orcid.org/0000-0003-0339-2305"},"institutions":[{"id":"https://openalex.org/I92178344","display_name":"Anhui University of Technology","ror":"https://ror.org/02qdtrq21","country_code":"CN","type":"education","lineage":["https://openalex.org/I92178344"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tianya You","raw_affiliation_strings":["School of Mechanical Engineering, Anhui University of Technology,Ma'anshan,Anhui,China,243002"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Anhui University of Technology,Ma'anshan,Anhui,China,243002","institution_ids":["https://openalex.org/I92178344"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102020756","display_name":"Xiangrong Xu","orcid":"https://orcid.org/0000-0001-6055-6797"},"institutions":[{"id":"https://openalex.org/I92178344","display_name":"Anhui University of Technology","ror":"https://ror.org/02qdtrq21","country_code":"CN","type":"education","lineage":["https://openalex.org/I92178344"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangrong Xu","raw_affiliation_strings":["School of Mechanical Engineering, Anhui University of Technology,Ma'anshan,Anhui,China,243002"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Anhui University of Technology,Ma'anshan,Anhui,China,243002","institution_ids":["https://openalex.org/I92178344"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000024068","display_name":"Hui Zhang","orcid":"https://orcid.org/0000-0002-5936-6571"},"institutions":[{"id":"https://openalex.org/I92178344","display_name":"Anhui University of Technology","ror":"https://ror.org/02qdtrq21","country_code":"CN","type":"education","lineage":["https://openalex.org/I92178344"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui Zhang","raw_affiliation_strings":["School of Mechanical Engineering, Anhui University of Technology,Ma'anshan,Anhui,China,243002"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Anhui University of Technology,Ma'anshan,Anhui,China,243002","institution_ids":["https://openalex.org/I92178344"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077817689","display_name":"Qingsong Yu","orcid":"https://orcid.org/0000-0002-6985-5969"},"institutions":[{"id":"https://openalex.org/I92178344","display_name":"Anhui University of Technology","ror":"https://ror.org/02qdtrq21","country_code":"CN","type":"education","lineage":["https://openalex.org/I92178344"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingsong Yu","raw_affiliation_strings":["School of Mechanical Engineering, Anhui University of Technology,Ma'anshan,Anhui,China,243002"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Anhui University of Technology,Ma'anshan,Anhui,China,243002","institution_ids":["https://openalex.org/I92178344"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069527664","display_name":"Aleksandar Rodi\u0107","orcid":"https://orcid.org/0000-0002-5595-9724"},"institutions":[{"id":"https://openalex.org/I4068193","display_name":"University of Belgrade","ror":"https://ror.org/02qsmb048","country_code":"RS","type":"education","lineage":["https://openalex.org/I4068193"]}],"countries":["RS"],"is_corresponding":false,"raw_author_name":"Aleksandar Rodic","raw_affiliation_strings":["University of Belgrade,Belgrade,Serbia,11120"],"affiliations":[{"raw_affiliation_string":"University of Belgrade,Belgrade,Serbia,11120","institution_ids":["https://openalex.org/I4068193"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044894804","display_name":"Petar B. Petrovi\u0107","orcid":"https://orcid.org/0000-0002-5375-600X"},"institutions":[{"id":"https://openalex.org/I4068193","display_name":"University of Belgrade","ror":"https://ror.org/02qsmb048","country_code":"RS","type":"education","lineage":["https://openalex.org/I4068193"]}],"countries":["RS"],"is_corresponding":false,"raw_author_name":"Petar B. Petrovic","raw_affiliation_strings":["University of Belgrade,Belgrade,Serbia,11120"],"affiliations":[{"raw_affiliation_string":"University of Belgrade,Belgrade,Serbia,11120","institution_ids":["https://openalex.org/I4068193"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5066561534"],"corresponding_institution_ids":["https://openalex.org/I92178344"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11564007,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"539","last_page":"544"},"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9448000192642212,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9430000185966492,"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/computer-science","display_name":"Computer science","score":0.8404208421707153},{"id":"https://openalex.org/keywords/grasp","display_name":"GRASP","score":0.8178759813308716},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7320811152458191},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6663156747817993},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.6217555403709412},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5793718099594116},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.5553688406944275},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5270070433616638},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5080556869506836},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.4921724200248718},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.46375468373298645},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4248700737953186},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35638344287872314}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8404208421707153},{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.8178759813308716},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7320811152458191},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6663156747817993},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.6217555403709412},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5793718099594116},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.5553688406944275},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5270070433616638},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5080556869506836},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.4921724200248718},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.46375468373298645},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4248700737953186},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35638344287872314},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icarm58088.2023.10218848","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icarm58088.2023.10218848","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Conference on Advanced Robotics and Mechatronics (ICARM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5600000023841858,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G3026609474","display_name":null,"funder_award_id":"2017YFE0113200","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W603908379","https://openalex.org/W1892339738","https://openalex.org/W1999156278","https://openalex.org/W2076363786","https://openalex.org/W2485911221","https://openalex.org/W2523315006","https://openalex.org/W2600030077","https://openalex.org/W2736762515","https://openalex.org/W2752782242","https://openalex.org/W2824754393","https://openalex.org/W2884585870","https://openalex.org/W2914944935","https://openalex.org/W2963033241","https://openalex.org/W2963326767","https://openalex.org/W2963495494","https://openalex.org/W3000909746","https://openalex.org/W3004284873","https://openalex.org/W3013482323","https://openalex.org/W3093541138","https://openalex.org/W3130885760","https://openalex.org/W3206386518","https://openalex.org/W6618372016","https://openalex.org/W6753412334"],"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/W3021551196"],"abstract_inverted_index":{"The":[0],"skill":[1],"of":[2,6,51,59,88,105,118,120],"grasping":[3,26,32,35,80],"is":[4,66],"one":[5],"fundamental":[7],"and":[8,34,55,97,129,140],"primary":[9],"skills":[10],"for":[11,23,74],"a":[12,19,44],"robot.":[13],"In":[14],"this":[15],"work,":[16],"we":[17,109],"present":[18],"lightweight":[20],"one-stage":[21],"algorithm":[22],"generating":[24],"robot":[25],"pose":[27,33,81],"estimates,":[28],"which":[29],"outputs":[30],"the":[31,49,60,103,111,121,133,137,142,148],"quality":[36],"predictions":[37],"on":[38],"each":[39],"pixel":[40],"directly":[41],"end-to-end":[42],"through":[43],"backbone":[45],"network.":[46],"To":[47],"address":[48],"problems":[50],"long":[52],"detection":[53,62,144],"time":[54],"large":[56],"computational":[57,149],"effort":[58],"two-target":[61],"algorithm,":[63],"pixel-level":[64],"learning":[65],"performed":[67],"by":[68],"combining":[69],"an":[70],"improved":[71],"Dense-Attention":[72],"module":[73],"deep":[75],"feature":[76],"extraction":[77],"to":[78,84,132,151],"achieve":[79],"estimation.":[82],"Compared":[83],"other":[85],"complex":[86],"architectures":[87],"similar":[89],"grasp":[90],"networks":[91],"our":[92],"network":[93],"has":[94],"fewer":[95],"parameters":[96],"detects":[98],"quickly":[99],"thus":[100],"better":[101],"meeting":[102],"requirements":[104],"real-time":[106],"detection.":[107],"Furthermore,":[108],"investigate":[110],"different":[112],"input":[113,126],"data":[114,128,131],"impact":[115],"in":[116],"terms":[117],"performance":[119,139],"algorithm.":[122],"We":[123],"find":[124],"that":[125],"depth":[127],"RGB":[130],"method":[134],"can":[135],"get":[136],"best":[138],"achieves":[141],"highest":[143],"accuracy,":[145],"despite":[146],"reducing":[147],"speed":[150],"some":[152],"extent.":[153]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}