{"id":"https://openalex.org/W4416251852","doi":"https://doi.org/10.1109/ijcnn64981.2025.11229063","title":"MSFF-SNet: An End-to-end Object Sorting Model with Multi-head Self-attention and Multi-scale Feature Fusion","display_name":"MSFF-SNet: An End-to-end Object Sorting Model with Multi-head Self-attention and Multi-scale Feature Fusion","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416251852","doi":"https://doi.org/10.1109/ijcnn64981.2025.11229063"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11229063","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11229063","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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/A5101514200","display_name":"Xiaoya Fan","orcid":"https://orcid.org/0000-0003-1702-4415"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoya Fan","raw_affiliation_strings":["Dalian University of Technology,School of Software,Dalian,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dalian University of Technology,School of Software,Dalian,China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jiaxiao Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaxiao Wang","raw_affiliation_strings":["Dalian University of Technology,School of Software,Dalian,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dalian University of Technology,School of Software,Dalian,China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115694817","display_name":"Zilu Wang","orcid":"https://orcid.org/0009-0004-0144-6888"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zilu Wang","raw_affiliation_strings":["Dalian University of Technology,School of Software,Dalian,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dalian University of Technology,School of Software,Dalian,China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090846161","display_name":"Zhonghua Huang","orcid":"https://orcid.org/0000-0002-2627-411X"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhonghua Huang","raw_affiliation_strings":["Dalian University of Technology,School of Software,Dalian,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dalian University of Technology,School of Software,Dalian,China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101736645","display_name":"Wenjie Yang","orcid":"https://orcid.org/0000-0002-4166-3850"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenjie Yang","raw_affiliation_strings":["Dalian University of Technology,School of Software,Dalian,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dalian University of Technology,School of Software,Dalian,China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101426707","display_name":"Wang Zhong","orcid":"https://orcid.org/0009-0002-5262-1928"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhong Wang","raw_affiliation_strings":["Dalian University of Technology,School of Software,Dalian,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dalian University of Technology,School of Software,Dalian,China","institution_ids":["https://openalex.org/I27357992"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I27357992"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9229000210762024,"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":0.9229000210762024,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.024299999698996544,"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"}},{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":0.009600000455975533,"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":0.8978999853134155},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6901000142097473},{"id":"https://openalex.org/keywords/sorting","display_name":"Sorting","score":0.5623999834060669},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5346999764442444},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.499099999666214},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.461899995803833},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4368000030517578},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3488999903202057}],"concepts":[{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.8978999853134155},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.79830002784729},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6901000142097473},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6897000074386597},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6809999942779541},{"id":"https://openalex.org/C111696304","wikidata":"https://www.wikidata.org/wiki/Q2303697","display_name":"Sorting","level":2,"score":0.5623999834060669},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5346999764442444},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.499099999666214},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.461899995803833},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4368000030517578},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3488999903202057},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.3375999927520752},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.33180001378059387},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.3264999985694885},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.32440000772476196},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.3116999864578247},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.2858000099658966},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2671000063419342},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.265500009059906},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25850000977516174}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11229063","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11229063","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1892339738","https://openalex.org/W1999156278","https://openalex.org/W2005824379","https://openalex.org/W2194775991","https://openalex.org/W2773072043","https://openalex.org/W2824754393","https://openalex.org/W2914433398","https://openalex.org/W2963150697","https://openalex.org/W2963326767","https://openalex.org/W3004280398","https://openalex.org/W3004284873","https://openalex.org/W3090139892","https://openalex.org/W3096609285","https://openalex.org/W3130885760","https://openalex.org/W3138516171","https://openalex.org/W3170679572","https://openalex.org/W3174873843","https://openalex.org/W3199093552","https://openalex.org/W3200697468","https://openalex.org/W4221167790","https://openalex.org/W4289656430","https://openalex.org/W4313472359","https://openalex.org/W4386916215","https://openalex.org/W4402754006"],"related_works":[],"abstract_inverted_index":{"Robotic":[0],"arm":[1],"sorting":[2],"aims":[3],"to":[4,14,70,120],"determine":[5],"the":[6,68,95,139,153,159,165,170],"optimal":[7],"grasping":[8,126],"poses":[9,61,127],"and":[10,21,35,50,85,128,143],"categories":[11],"of":[12,79,101,125,136,150],"objects":[13,24,69],"be":[15,71],"sorted":[16],"based":[17],"on":[18,138,152,169],"perception":[19],"information":[20],"then":[22,105],"place":[23],"into":[25],"corresponding":[26],"positions.":[27],"Most":[28],"methods":[29],"combine":[30],"an":[31],"object":[32,129],"detection":[33,38,116],"algorithm":[34,39],"a":[36,42,80,91,108,114,133,144],"grasp":[37,48,60,134],"sequentially.":[40],"Such":[41],"two-stage":[43],"strategy":[44],"results":[45],"in":[46],"unsatisfactory":[47],"accuracy":[49,135],"speed.":[51],"This":[52],"paper":[53],"proposes":[54],"MSFF-SNet,":[55],"which":[56],"directly":[57,121],"work":[58],"with":[59,148],"as":[62],"learning":[63],"targets,":[64],"while":[65],"simultaneously":[66],"recognizing":[67],"sorted.":[72],"Specifically,":[73],"multi-scale":[74],"features":[75,87,100],"from":[76],"different":[77],"layers":[78],"ResNet50":[81],"are":[82,88,104],"first":[83],"extracted":[84],"intra-scale":[86],"fused":[89,106],"using":[90],"self-attention":[92],"mechanism,":[93],"emphasizing":[94],"global":[96],"contextual":[97],"information.":[98],"The":[99,175],"multiple":[102],"scales":[103],"through":[107],"cross-scale":[109],"feature":[110],"fusion":[111],"module.":[112],"Finally,":[113],"multi-task":[115],"head":[117],"is":[118,177],"used":[119],"make":[122],"pixel-level":[123],"predictions":[124],"categories.":[130],"MSFF-SNet":[131],"achieved":[132,164],"99.62%":[137],"Cornell":[140],"Grasping":[141],"Dataset":[142],"mean":[145],"Average":[146],"Precision":[147],"Grasp":[149],"79.52%":[151],"Visual":[154,171],"Manipulation":[155,172],"Relationship":[156,173],"Dataset,":[157],"achieving":[158],"state-of-the-art":[160],"performance.":[161],"Besides,":[162],"it":[163],"highest":[166],"inference":[167],"speed":[168],"Dataset.":[174],"code":[176],"available":[178],"at":[179],"https://github.com/wzhy2000/MSFF-SNet.":[180]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-11-14T00:00:00"}