{"id":"https://openalex.org/W4409484364","doi":"https://doi.org/10.3390/sym17040602","title":"Feature Symmetry Fusion Remote Sensing Detection Network Based on Spatial Adaptive Selection","display_name":"Feature Symmetry Fusion Remote Sensing Detection Network Based on Spatial Adaptive Selection","publication_year":2025,"publication_date":"2025-04-16","ids":{"openalex":"https://openalex.org/W4409484364","doi":"https://doi.org/10.3390/sym17040602"},"language":"en","primary_location":{"id":"doi:10.3390/sym17040602","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym17040602","pdf_url":"https://www.mdpi.com/2073-8994/17/4/602/pdf?version=1744800343","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2073-8994/17/4/602/pdf?version=1744800343","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101982803","display_name":"Heng Xiao","orcid":"https://orcid.org/0000-0002-8384-4027"},"institutions":[{"id":"https://openalex.org/I4210149102","display_name":"Sanya University","ror":"https://ror.org/04fa2qd52","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210149102"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Heng Xiao","raw_affiliation_strings":["Academician Rong Chunmin Workstation, University of Sanya, Sanya 572022, China","School of Information and Intelligent Engineering, University of Sanya, Sanya 572022, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Academician Rong Chunmin Workstation, University of Sanya, Sanya 572022, China","institution_ids":["https://openalex.org/I4210149102"]},{"raw_affiliation_string":"School of Information and Intelligent Engineering, University of Sanya, Sanya 572022, China","institution_ids":["https://openalex.org/I4210149102"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024498727","display_name":"Donglin Jing","orcid":"https://orcid.org/0000-0003-3021-5371"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Donglin Jing","raw_affiliation_strings":["Shanghai Aerospace Control Technology Institute, Shanghai 201109, China"],"raw_orcid":"https://orcid.org/0000-0003-3021-5371","affiliations":[{"raw_affiliation_string":"Shanghai Aerospace Control Technology Institute, Shanghai 201109, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100329781","display_name":"Fujun Zhao","orcid":"https://orcid.org/0000-0002-9518-6279"},"institutions":[{"id":"https://openalex.org/I4210149102","display_name":"Sanya University","ror":"https://ror.org/04fa2qd52","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210149102"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fujun Zhao","raw_affiliation_strings":["School of Information and Intelligent Engineering, University of Sanya, Sanya 572022, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Intelligent Engineering, University of Sanya, Sanya 572022, China","institution_ids":["https://openalex.org/I4210149102"]}]},{"author_position":"last","author":{"id":null,"display_name":"Shaokang Zha","orcid":null},"institutions":[{"id":"https://openalex.org/I4210149102","display_name":"Sanya University","ror":"https://ror.org/04fa2qd52","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210149102"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaokang Zha","raw_affiliation_strings":["School of Information and Intelligent Engineering, University of Sanya, Sanya 572022, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Intelligent Engineering, University of Sanya, Sanya 572022, China","institution_ids":["https://openalex.org/I4210149102"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5024498727"],"corresponding_institution_ids":[],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":0.923,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.75446447,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"17","issue":"4","first_page":"602","last_page":"602"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9959999918937683,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9909999966621399,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6358575224876404},{"id":"https://openalex.org/keywords/symmetry","display_name":"Symmetry (geometry)","score":0.561371922492981},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5601988434791565},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5559979677200317},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5471514463424683},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5358542203903198},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.5192942023277283},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.518059492111206},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5158402323722839},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.40526506304740906},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2661709785461426},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.12581247091293335}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6358575224876404},{"id":"https://openalex.org/C2779886137","wikidata":"https://www.wikidata.org/wiki/Q21030012","display_name":"Symmetry (geometry)","level":2,"score":0.561371922492981},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5601988434791565},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5559979677200317},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5471514463424683},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5358542203903198},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5192942023277283},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.518059492111206},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5158402323722839},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.40526506304740906},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2661709785461426},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.12581247091293335},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3390/sym17040602","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym17040602","pdf_url":"https://www.mdpi.com/2073-8994/17/4/602/pdf?version=1744800343","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.3390/sym17040602","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym17040602","pdf_url":"https://www.mdpi.com/2073-8994/17/4/602/pdf?version=1744800343","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4409484364.pdf","grobid_xml":"https://content.openalex.org/works/W4409484364.grobid-xml"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2162915993","https://openalex.org/W2193145675","https://openalex.org/W2296151615","https://openalex.org/W2565639579","https://openalex.org/W2594177559","https://openalex.org/W2768489488","https://openalex.org/W2949058942","https://openalex.org/W2962721361","https://openalex.org/W2962749812","https://openalex.org/W2963091558","https://openalex.org/W2963790522","https://openalex.org/W2964979676","https://openalex.org/W2966926453","https://openalex.org/W2968292493","https://openalex.org/W2991359031","https://openalex.org/W3015331846","https://openalex.org/W3016780015","https://openalex.org/W3021737887","https://openalex.org/W3027940006","https://openalex.org/W3034421924","https://openalex.org/W3106250896","https://openalex.org/W3109055651","https://openalex.org/W3111729930","https://openalex.org/W3119027652","https://openalex.org/W3121842289","https://openalex.org/W3134025014","https://openalex.org/W3136761610","https://openalex.org/W3141404903","https://openalex.org/W3170033848","https://openalex.org/W3176859937","https://openalex.org/W3180084293","https://openalex.org/W3203608457","https://openalex.org/W4210925408","https://openalex.org/W4214535086","https://openalex.org/W4214648418","https://openalex.org/W4283800076","https://openalex.org/W4290832506","https://openalex.org/W4319450743","https://openalex.org/W4395482151","https://openalex.org/W4400808535","https://openalex.org/W4408781534","https://openalex.org/W6770689091","https://openalex.org/W6782137339","https://openalex.org/W6791464520","https://openalex.org/W6798229470"],"related_works":["https://openalex.org/W3147584709","https://openalex.org/W2099421762","https://openalex.org/W2530546662","https://openalex.org/W2967030268","https://openalex.org/W2132659060","https://openalex.org/W2031992971","https://openalex.org/W4386564352","https://openalex.org/W3214791684","https://openalex.org/W2952668426","https://openalex.org/W2152662039"],"abstract_inverted_index":{"This":[0,59,147],"paper":[1],"proposes":[2],"a":[3,12,19,27,50,88],"spatially":[4],"adaptive":[5,142],"feature":[6,75,128,137,167],"fine":[7,135],"fusion":[8],"network":[9,68],"consisting":[10],"of":[11,65,78,122,144],"Fast":[13],"Convolution":[14],"Decomposition":[15],"Sequence":[16],"(FCDS)":[17],"and":[18,71,119,139,172],"Spatial":[20],"Selection":[21],"Mechanism":[22],"(SSM).":[23],"Firstly,":[24],"in":[25,97,126,169],"FCDS,":[26],"large":[28],"kernel":[29,52,85,98],"convolution":[30,39,84],"decomposition":[31],"operation":[32],"is":[33,112],"used":[34,192],"to":[35,54,114,133,160,202],"break":[36],"down":[37],"dense":[38],"kernels":[40],"into":[41],"small":[42],"convolutions":[43],"with":[44,185],"gradually":[45],"increasing":[46],"hole":[47],"rates,":[48],"forming":[49],"continuous":[51],"sequence":[53,86],"obtain":[55],"finer":[56],"scale":[57,136],"features.":[58],"approach":[60],"significantly":[61],"reduces":[62],"the":[63,73,79,82,108,116,123,127,141],"number":[64],"parameters,":[66],"improves":[67],"inference":[69],"efficiency,":[70],"preserves":[72],"spatial":[74,109,158,173],"expression":[76],"ability":[77,143],"network.":[80],"Notably,":[81],"decomposed":[83],"adopts":[87],"symmetric":[89,150,163],"dilation":[90],"rate":[91],"increment":[92],"strategy,":[93],"maintaining":[94],"symmetry":[95],"constraints":[96],"weight":[99,152],"distribution":[100],"while":[101],"expanding":[102],"receptive":[103],"fields.":[104],"On":[105],"this":[106],"basis,":[107],"selection":[110],"mechanism":[111,148],"utilized":[113],"enhance":[115],"key":[117],"features":[118],"background":[120],"differences":[121],"target":[124,195],"location":[125],"map,":[129],"dynamically":[130],"allocate":[131],"weights":[132],"different":[134],"maps,":[138],"improve":[140],"multi-scale":[145],"domains.":[146],"employs":[149],"attention":[151,156],"allocation":[153],"(symmetric":[154],"channel":[155,171],"+":[157],"attention)":[159],"establish":[161],"complementary":[162],"response":[164],"patterns":[165],"across":[166],"maps":[168],"both":[170],"dimensions.":[174],"Numerous":[175],"experiments":[176],"have":[177],"shown":[178],"that":[179],"our":[180],"method":[181],"achieves":[182],"higher":[183],"performance":[184],"81.64%,":[186],"91.34%,":[187],"91.20%mAP":[188],"on":[189],"three":[190],"commonly":[191],"remote":[193],"sensing":[194],"datasets":[196],"(DOTA,":[197],"UCAS":[198],"AOD,":[199],"HRSC2016)":[200],"compared":[201],"existing":[203],"advanced":[204],"detection":[205],"networks.":[206]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}