{"id":"https://openalex.org/W4402610783","doi":"https://doi.org/10.1017/s0263574724001358","title":"A pixel-level grasp detection method based on Efficient Grasp Aware Network","display_name":"A pixel-level grasp detection method based on Efficient Grasp Aware Network","publication_year":2024,"publication_date":"2024-09-01","ids":{"openalex":"https://openalex.org/W4402610783","doi":"https://doi.org/10.1017/s0263574724001358"},"language":"en","primary_location":{"id":"doi:10.1017/s0263574724001358","is_oa":false,"landing_page_url":"https://doi.org/10.1017/s0263574724001358","pdf_url":null,"source":{"id":"https://openalex.org/S92163612","display_name":"Robotica","issn_l":"0263-5747","issn":["0263-5747","1469-8668"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311721","host_organization_name":"Cambridge University Press","host_organization_lineage":["https://openalex.org/P4310311721","https://openalex.org/P4310311702"],"host_organization_lineage_names":["Cambridge University Press","University of Cambridge"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Robotica","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/A5082437771","display_name":"Haonan Xi","orcid":"https://orcid.org/0009-0004-8490-4900"},"institutions":[{"id":"https://openalex.org/I150807315","display_name":"Guangxi University","ror":"https://ror.org/02c9qn167","country_code":"CN","type":"education","lineage":["https://openalex.org/I150807315"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haonan Xi","raw_affiliation_strings":["School of Electrical Engineering, Guangxi University, Nanning, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Guangxi University, Nanning, China","institution_ids":["https://openalex.org/I150807315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057147579","display_name":"Shaodong Li","orcid":"https://orcid.org/0000-0002-5034-8721"},"institutions":[{"id":"https://openalex.org/I150807315","display_name":"Guangxi University","ror":"https://ror.org/02c9qn167","country_code":"CN","type":"education","lineage":["https://openalex.org/I150807315"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shaodong Li","raw_affiliation_strings":["School of Electrical Engineering, Guangxi University, Nanning, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Guangxi University, Nanning, China","institution_ids":["https://openalex.org/I150807315"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100632342","display_name":"Liu Xi","orcid":"https://orcid.org/0000-0002-2604-3194"},"institutions":[{"id":"https://openalex.org/I150807315","display_name":"Guangxi University","ror":"https://ror.org/02c9qn167","country_code":"CN","type":"education","lineage":["https://openalex.org/I150807315"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xi Liu","raw_affiliation_strings":["School of Electrical Engineering, Guangxi University, Nanning, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Guangxi University, Nanning, China","institution_ids":["https://openalex.org/I150807315"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5057147579"],"corresponding_institution_ids":["https://openalex.org/I150807315"],"apc_list":null,"apc_paid":null,"fwci":1.558,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.83276644,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"42","issue":"9","first_page":"3190","last_page":"3210"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9661999940872192,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9661999940872192,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T13731","display_name":"Advanced Computing and Algorithms","score":0.9524000287055969,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9453999996185303,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/grasp","display_name":"GRASP","score":0.9747422933578491},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6829585433006287},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6036471128463745},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5691603422164917},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4738224744796753}],"concepts":[{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.9747422933578491},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6829585433006287},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6036471128463745},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5691603422164917},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4738224744796753},{"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:10.1017/s0263574724001358","is_oa":false,"landing_page_url":"https://doi.org/10.1017/s0263574724001358","pdf_url":null,"source":{"id":"https://openalex.org/S92163612","display_name":"Robotica","issn_l":"0263-5747","issn":["0263-5747","1469-8668"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311721","host_organization_name":"Cambridge University Press","host_organization_lineage":["https://openalex.org/P4310311721","https://openalex.org/P4310311702"],"host_organization_lineage_names":["Cambridge University Press","University of Cambridge"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Robotica","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2963326767","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2772917594","https://openalex.org/W2775347418","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747"],"abstract_inverted_index":{"Abstract":[0],"This":[1],"work":[2],"proposes":[3],"a":[4,130],"novel":[5],"grasp":[6,18,72,126,157],"detection":[7],"method,":[8],"the":[9,41,48,71,85,120,124],"Efficient":[10],"Grasp":[11],"Aware":[12],"Network":[13],"(EGA-Net),":[14],"for":[15,25,105],"robotic":[16,136],"visual":[17],"detection.":[19],"Our":[20,63],"method":[21,64,100,115],"obtains":[22,32],"semantic":[23],"information":[24],"grasping":[26,38,142],"through":[27,40],"feature":[28,33],"extraction.":[29],"It":[30],"efficiently":[31],"channel":[34],"weights":[35],"related":[36],"to":[37,55,108,138],"tasks":[39],"constructed":[42],"ECA-ResNet":[43],"module,":[44],"which":[45],"can":[46,155],"smooth":[47],"network\u2019s":[49],"learning.":[50],"Meanwhile,":[51],"we":[52,91,128],"use":[53,129],"concatenation":[54],"obtain":[56],"low-level":[57],"features":[58],"with":[59],"rich":[60],"spatial":[61],"information.":[62],"inputs":[65],"an":[66,110],"RGB-D":[67,111],"image":[68],"and":[69,74,82,87,90,94,175],"outputs":[70],"poses":[73],"their":[75],"quality":[76],"score.":[77],"The":[78,98,167],"EGA-Net":[79],"is":[80],"trained":[81],"tested":[83],"on":[84],"Cornell":[86],"Jacquard":[88],"datasets,":[89],"achieve":[92],"98.9%":[93],"95.8%":[95],"accuracy,":[96],"respectively.":[97],"proposed":[99],"only":[101],"takes":[102],"24":[103],"ms":[104],"real-time":[106],"performance":[107],"process":[109],"image.":[112],"Moreover,":[113],"our":[114,153,171],"achieved":[116],"better":[117],"results":[118,169],"in":[119,146,165],"comparison":[121],"experiment.":[122],"In":[123],"real-world":[125],"experiments,":[127],"6-degree":[131],"of":[132,143,160],"freedom":[133],"(DOF)":[134],"UR-5":[135],"arm":[137],"demonstrate":[139,151],"its":[140],"robust":[141],"unseen":[144],"objects":[145,161],"various":[147],"scenes.":[148],"We":[149],"also":[150],"that":[152],"model":[154],"successfully":[156],"different":[158],"types":[159],"without":[162],"any":[163],"processing":[164],"advance.":[166],"experiment":[168],"validate":[170],"model\u2019s":[172],"exceptional":[173],"robustness":[174],"generalization.":[176]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-09T08:58:05.943551","created_date":"2025-10-10T00:00:00"}
