{"id":"https://openalex.org/W4415626520","doi":"https://doi.org/10.1109/taes.2025.3626311","title":"TCINet: Transformer\u2013CNN Interaction Network for Space Noncooperative Object Saliency Detection","display_name":"TCINet: Transformer\u2013CNN Interaction Network for Space Noncooperative Object Saliency Detection","publication_year":2025,"publication_date":"2025-10-28","ids":{"openalex":"https://openalex.org/W4415626520","doi":"https://doi.org/10.1109/taes.2025.3626311"},"language":null,"primary_location":{"id":"doi:10.1109/taes.2025.3626311","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taes.2025.3626311","pdf_url":null,"source":{"id":"https://openalex.org/S193624734","display_name":"IEEE Transactions on Aerospace and Electronic Systems","issn_l":"0018-9251","issn":["0018-9251","1557-9603","2371-9877"],"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 Aerospace and Electronic Systems","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/A5100618023","display_name":"Menghan Wang","orcid":"https://orcid.org/0000-0003-0809-8818"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Menghan Wang","raw_affiliation_strings":["School of Aerospace Science and Technology, Xidian University, Xi’an, China","School of Aerospace Science and Technology, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Aerospace Science and Technology, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Aerospace Science and Technology, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076897920","display_name":"Dongzhu Feng","orcid":"https://orcid.org/0000-0001-5467-2759"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongzhu Feng","raw_affiliation_strings":["School of Aerospace Science and Technology, Xidian University, Xi’an, China","School of Aerospace Science and Technology, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Aerospace Science and Technology, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Aerospace Science and Technology, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011947035","display_name":"Pei Dai","orcid":"https://orcid.org/0000-0003-0469-6570"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pei Dai","raw_affiliation_strings":["School of Aerospace Science and Technology, Xidian University, Xi’an, China","School of Aerospace Science and Technology, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Aerospace Science and Technology, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Aerospace Science and Technology, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085946551","display_name":"Hanlin Qin","orcid":"https://orcid.org/0009-0009-0412-0345"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanlin Qin","raw_affiliation_strings":["School of Aerospace Science and Technology, Xidian University, Xi’an, China","School of Optoelectronic Engineering, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Aerospace Science and Technology, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Optoelectronic Engineering, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029238738","display_name":"Hehe Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hehe Guo","raw_affiliation_strings":["School of Aerospace Science and Technology, Xidian University, Xi’an, China","School of Aerospace Science and Technology, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Aerospace Science and Technology, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Aerospace Science and Technology, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100618023"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.30501417,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"62","issue":null,"first_page":"913","last_page":"928"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9218999743461609,"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"}},"topics":[{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9218999743461609,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.04340000078082085,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.0020000000949949026,"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/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5008000135421753},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4950000047683716},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.44359999895095825},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.41839998960494995},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4108999967575073},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.40689998865127563},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.40059998631477356},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.3862999975681305},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.38339999318122864}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6758000254631042},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6507999897003174},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5026000142097473},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5008000135421753},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4950000047683716},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.44359999895095825},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.41839998960494995},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4108999967575073},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.40689998865127563},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.40059998631477356},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.3862999975681305},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.38339999318122864},{"id":"https://openalex.org/C99102927","wikidata":"https://www.wikidata.org/wiki/Q3058184","display_name":"Scale space","level":4,"score":0.3815000057220459},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.37630000710487366},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.3668999969959259},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.36579999327659607},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3562999963760376},{"id":"https://openalex.org/C88796919","wikidata":"https://www.wikidata.org/wiki/Q1142907","display_name":"Backbone network","level":2,"score":0.3546000123023987},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.35120001435279846},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.3409999907016754},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.336899995803833},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.33219999074935913},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.32749998569488525},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.3111000061035156},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.29420000314712524},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.29019999504089355},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.2827000021934509},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.2809999883174896},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25189998745918274}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/taes.2025.3626311","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taes.2025.3626311","pdf_url":null,"source":{"id":"https://openalex.org/S193624734","display_name":"IEEE Transactions on Aerospace and Electronic Systems","issn_l":"0018-9251","issn":["0018-9251","1557-9603","2371-9877"],"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 Aerospace and Electronic Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5586901205","display_name":null,"funder_award_id":"2021GY-0362","funder_id":"https://openalex.org/F4320336350","funder_display_name":"Key Research and Development Projects of Shaanxi Province"},{"id":"https://openalex.org/G6491132031","display_name":null,"funder_award_id":"62303363","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/F4320336350","display_name":"Key Research and Development Projects of Shaanxi Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W21025885","https://openalex.org/W639708223","https://openalex.org/W1982075130","https://openalex.org/W1994922096","https://openalex.org/W2014854862","https://openalex.org/W2039313011","https://openalex.org/W2047670868","https://openalex.org/W2128272608","https://openalex.org/W2194775991","https://openalex.org/W2944532584","https://openalex.org/W2963112696","https://openalex.org/W2963446712","https://openalex.org/W2963529609","https://openalex.org/W2998449272","https://openalex.org/W2998676925","https://openalex.org/W3025800305","https://openalex.org/W3092068882","https://openalex.org/W3112885960","https://openalex.org/W3113755791","https://openalex.org/W3122006940","https://openalex.org/W3136838953","https://openalex.org/W3138516171","https://openalex.org/W3149345112","https://openalex.org/W3160526953","https://openalex.org/W3175515048","https://openalex.org/W3176191528","https://openalex.org/W3177004386","https://openalex.org/W3190166470","https://openalex.org/W3190348190","https://openalex.org/W3203718853","https://openalex.org/W3217763214","https://openalex.org/W4206132833","https://openalex.org/W4214561053","https://openalex.org/W4224237609","https://openalex.org/W4250112989","https://openalex.org/W4301887611","https://openalex.org/W4313546627","https://openalex.org/W4313575385","https://openalex.org/W4319996201","https://openalex.org/W4380607206","https://openalex.org/W4386076434","https://openalex.org/W4387757595","https://openalex.org/W4392309443","https://openalex.org/W4392405950","https://openalex.org/W4399563113","https://openalex.org/W4400409506","https://openalex.org/W4402167570","https://openalex.org/W4402787649","https://openalex.org/W4403791281"],"related_works":[],"abstract_inverted_index":{"Space":[0,10],"Non-Cooperative":[1],"Object":[2,22],"Detection":[3,23],"(SNCOD)":[4],"is":[5,38,109],"an":[6],"essential":[7],"part":[8],"of":[9,19,66,141,148,157],"Situation":[11],"Awareness":[12],"(SSA).":[13],"The":[14,117,161],"localization":[15],"and":[16,58,100,104,129,143,175,198,246],"segmentation":[17],"capabilities":[18],"the":[20,63,67,81,120,124,130,138,145,154,187,207,231],"Salient":[21],"(SOD)":[24],"method":[25,69,233],"have":[26],"been":[27],"proven":[28],"effective":[29],"in":[30,41,70],"other":[31],"common":[32],"visual":[33],"tasks,":[34],"but":[35],"its":[36],"application":[37],"poorly":[39],"studied":[40],"SNCOD":[42,76],"tasks.":[43],"This":[44],"paper":[45],"first":[46],"conducts":[47],"extensive":[48],"comparative":[49],"experiments":[50,222],"using":[51],"state-of-the-art":[52,240],"SOD":[53,68,241],"methods":[54,242],"on":[55,80,223],"SwissCube,":[56],"Satellite":[57],"Speed+":[59],"datasets":[60,228],"to":[61,136,151,181,193,201,238],"investigate":[62],"generalization":[64,83],"ability":[65],"SNCOD,":[71],"providing":[72],"supports":[73],"for":[74,111],"subsequent":[75],"research.":[77],"Then,":[78],"based":[79],"above":[82],"analysis,":[84],"a":[85,95,101],"Transformer-Convolutional":[86],"Neural":[87],"Network":[88,91,127],"(CNN)":[89],"Interaction":[90],"(TCINet)":[92],"equipped":[93],"with":[94,153,243],"Transformer-CNN":[96],"Trilateral":[97],"Backbone":[98],"(TCTB)":[99],"Loop":[102],"View":[103],"Detail":[105,177],"compensation":[106],"Module":[107,134],"(LVDM)":[108],"proposed":[110,232],"space":[112,158,225],"non-cooperative":[113,159],"object":[114,226],"saliency":[115,212],"detection.":[116],"TCTB":[118],"incorporates":[119],"Pyramid":[121],"Transformer-in-Transformer":[122],"(PTNT),":[123],"Bilateral":[125],"Multi-scale":[126,176],"(BMN),":[128],"Multi-level":[131,170],"Cross-Complementary":[132],"Attention":[133],"(MCAM)":[135],"improve":[137],"multi-scale":[139],"adaptability":[140],"CNN":[142],"guide":[144],"semantic":[146],"modeling":[147],"CNN,":[149],"committed":[150],"coping":[152],"scale":[155],"diversity":[156],"objects.":[160],"LVDM":[162,188],"chains":[163],"different":[164,183,202],"dilated":[165],"convolutions,":[166],"Top-Down":[167],"Path":[168,191],"(TDP),":[169],"Feature-guided":[171],"Enhancement":[172,178],"(MFE)":[173],"block,":[174],"(MDE)":[179],"block":[180],"construct":[182],"decision":[184,203],"paths.":[185],"Further,":[186],"sets":[189],"Switch-Decision":[190],"(SDP)":[192],"assign":[194],"scale-specific":[195],"view":[196],"perception":[197],"fine-grained":[199],"enhancement":[200],"paths,":[204],"which":[205],"decodes":[206],"feature":[208],"set":[209],"into":[210],"precise":[211],"maps":[213],"through":[214],"setting":[215],"chained":[216],"recurrent":[217],"training.":[218],"Finally,":[219],"comprehensive":[220],"comparison":[221],"three":[224],"benchmark":[227],"demonstrate":[229],"that":[230],"achieves":[234],"superior":[235],"performance":[236],"comparable":[237],"extant":[239],"fewer":[244],"parameters":[245],"computational":[247],"burden.":[248]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-29T00:00:00"}