{"id":"https://openalex.org/W7138315419","doi":"https://doi.org/10.1609/aaai.v40i9.37698","title":"LWGANet: Addressing Spatial and Channel Redundancy in Remote Sensing Visual Tasks with Light-Weight Grouped Attention","display_name":"LWGANet: Addressing Spatial and Channel Redundancy in Remote Sensing Visual Tasks with Light-Weight Grouped Attention","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138315419","doi":"https://doi.org/10.1609/aaai.v40i9.37698"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v40i9.37698","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i9.37698","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1609/aaai.v40i9.37698","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129746745","display_name":"Wei Lu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei Lu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129693724","display_name":"Xue Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xue Yang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129693145","display_name":"Si-Bao Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Si-Bao Chen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":158.634,"has_fulltext":true,"cited_by_count":14,"citation_normalized_percentile":{"value":0.99946409,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":100},"biblio":{"volume":"40","issue":"9","first_page":"7574","last_page":"7582"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.6334999799728394,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.6334999799728394,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.17409999668598175,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.04729999974370003,"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/redundancy","display_name":"Redundancy (engineering)","score":0.8471999764442444},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.5644999742507935},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5382000207901001},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.46309998631477356},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4417000114917755},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.400299996137619},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35989999771118164}],"concepts":[{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.8471999764442444},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7833999991416931},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.5644999742507935},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5382000207901001},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.46309998631477356},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45969998836517334},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4417000114917755},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.400299996137619},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3869999945163727},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37400001287460327},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35989999771118164},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.32170000672340393},{"id":"https://openalex.org/C66882249","wikidata":"https://www.wikidata.org/wiki/Q169336","display_name":"Homogeneous","level":2,"score":0.31700000166893005},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3027999997138977},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.28850001096725464},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.28209999203681946},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.2793999910354614},{"id":"https://openalex.org/C183365957","wikidata":"https://www.wikidata.org/wiki/Q17140402","display_name":"Remote sensing application","level":3,"score":0.25690001249313354},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.2547999918460846},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.25040000677108765}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1609/aaai.v40i9.37698","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i9.37698","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:ojs.aaai.org:article/37698","is_oa":true,"landing_page_url":"https://ojs.aaai.org/index.php/AAAI/article/view/37698","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/37698/41660","source":{"id":"https://openalex.org/S7407064318","display_name":"AAAI Publications","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2159-5399","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i9.37698","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i9.37698","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2599639279","display_name":null,"funder_award_id":"U24A20342","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G427914820","display_name":null,"funder_award_id":"62506229","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4986787686","display_name":null,"funder_award_id":"62576006","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6226388984","display_name":null,"funder_award_id":"25ZR1402268","funder_id":"https://openalex.org/F4320309612","funder_display_name":"Natural Science Foundation of Shanghai"},{"id":"https://openalex.org/G6474056369","display_name":null,"funder_award_id":"61976004","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320309612","display_name":"Natural Science Foundation of Shanghai","ror":null},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Light-weight":[0],"neural":[1],"networks":[2],"for":[3,37,60,160],"remote":[4],"sensing":[5],"(RS)":[6],"visual":[7,162],"analysis":[8,163],"must":[9],"overcome":[10],"two":[11,65],"inherent":[12],"redundancies:":[13],"spatial":[14,77],"redundancy":[15,78,95],"from":[16],"vast,":[17],"homogeneous":[18],"backgrounds,":[19],"and":[20,85,118,138,151],"channel":[21,94],"redundancy,":[22],"where":[23],"extreme":[24],"scale":[25],"variations":[26],"render":[27],"a":[28,56,68,86,111,156],"single":[29],"feature":[30,115],"space":[31],"inefficient.":[32],"Existing":[33],"models,":[34],"often":[35],"designed":[36],"natural":[38],"images,":[39],"fail":[40],"to":[41],"address":[42],"this":[43,51],"dual":[44],"challenge":[45],"in":[46,148,164],"RS":[47,130,165],"scenarios.":[48],"To":[49],"bridge":[50],"gap,":[52],"we":[53],"propose":[54],"LWGANet,":[55],"light-weight":[57,146],"backbone":[58],"engineered":[59],"RS-specific":[61],"properties.":[62],"LWGANet":[63,109,142],"introduces":[64],"core":[66,107],"innovations:":[67],"Top-K":[69],"Global":[70],"Feature":[71],"Interaction":[72],"(TGFI)":[73],"module":[74,91],"that":[75,92,141],"mitigates":[76],"by":[79,96],"focusing":[80],"computation":[81],"on":[82,123],"salient":[83],"regions,":[84],"Light-Weight":[87],"Grouped":[88],"Attention":[89],"(LWGA)":[90],"resolves":[93],"partitioning":[97],"channels":[98],"into":[99],"specialized,":[100],"scale-specific":[101],"pathways.":[102],"By":[103],"synergistically":[104],"resolving":[105],"these":[106],"inefficiencies,":[108],"achieves":[110],"superior":[112],"trade-off":[113],"between":[114],"representation":[116],"quality":[117],"computational":[119],"cost.":[120],"Extensive":[121],"experiments":[122],"twelve":[124],"diverse":[125],"datasets":[126],"across":[127],"four":[128],"major":[129],"tasks\u2014scene":[131],"classification,":[132],"oriented":[133],"object":[134],"detection,":[135],"semantic":[136],"segmentation,":[137],"change":[139],"detection\u2014demonstrate":[140],"consistently":[143],"outperforms":[144],"state-of-the-art":[145],"backbones":[147],"both":[149],"accuracy":[150],"efficiency.":[152],"Our":[153],"work":[154],"establishes":[155],"new,":[157],"robust":[158],"baseline":[159],"efficient":[161],"images.":[166]},"counts_by_year":[{"year":2026,"cited_by_count":13},{"year":2025,"cited_by_count":1}],"updated_date":"2026-09-02T07:38:04.252551","created_date":"2026-03-18T00:00:00"}