{"id":"https://openalex.org/W7127054506","doi":"https://doi.org/10.1145/3784833.3784923","title":"Lightweight Intelligent Task Classification Model for Heterogeneous Data in Non-Terrestrial Networks","display_name":"Lightweight Intelligent Task Classification Model for Heterogeneous Data in Non-Terrestrial Networks","publication_year":2025,"publication_date":"2025-11-12","ids":{"openalex":"https://openalex.org/W7127054506","doi":"https://doi.org/10.1145/3784833.3784923"},"language":null,"primary_location":{"id":"doi:10.1145/3784833.3784923","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3784833.3784923","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 11th International Conference on Communication and Information Processing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3784833.3784923","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5124724930","display_name":"Zichao Qin","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zichao Qin","raw_affiliation_strings":["Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0001-6643-5918","affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100346472","display_name":"Rong Liu","orcid":"https://orcid.org/0009-0004-2484-5080"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rongke Liu","raw_affiliation_strings":["Beihang University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0004-2484-5080","affiliations":[{"raw_affiliation_string":"Beihang University, Shenzhen, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029502702","display_name":"Ling Zhao","orcid":"https://orcid.org/0000-0001-5834-2271"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ling Zhao","raw_affiliation_strings":["Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-5834-2271","affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124710708","display_name":"Da Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Da Xu","raw_affiliation_strings":["Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0007-4808-0002","affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124715962","display_name":"Tong Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tong Wu","raw_affiliation_strings":["China Satellite Network Group Co., Ltd, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0007-5485-2232","affiliations":[{"raw_affiliation_string":"China Satellite Network Group Co., Ltd, Beijing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.77405675,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"440","last_page":"446"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11133","display_name":"UAV Applications and Optimization","score":0.2703999876976013,"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"}},"topics":[{"id":"https://openalex.org/T11133","display_name":"UAV Applications and Optimization","score":0.2703999876976013,"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"}},{"id":"https://openalex.org/T13918","display_name":"Advanced Data and IoT Technologies","score":0.12290000170469284,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10036","display_name":"Advanced Neural Network Applications","score":0.07280000299215317,"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/discriminative-model","display_name":"Discriminative model","score":0.6098999977111816},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.5990999937057495},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5770999789237976},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.5166000127792358},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4894999861717224},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4553999900817871},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4494999945163727},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4487000107765198},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4417000114917755}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8113999962806702},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6098999977111816},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.5990999937057495},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5770999789237976},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.5166000127792358},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.510200023651123},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4894999861717224},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4666000008583069},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4553999900817871},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4494999945163727},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4487000107765198},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4417000114917755},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4056999981403351},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.39100000262260437},{"id":"https://openalex.org/C43364308","wikidata":"https://www.wikidata.org/wiki/Q8799","display_name":"Byte","level":2,"score":0.36959999799728394},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.36730000376701355},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3644999861717224},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.3483999967575073},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.33239999413490295},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3158000111579895},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.30309998989105225},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.30070000886917114},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.28600001335144043},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.2827000021934509},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.27799999713897705},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.2547000050544739},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.25099998712539673},{"id":"https://openalex.org/C2780724565","wikidata":"https://www.wikidata.org/wiki/Q5227256","display_name":"Data classification","level":2,"score":0.25099998712539673},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.2506999969482422}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3784833.3784923","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3784833.3784923","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 11th International Conference on Communication and Information Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3784833.3784923","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3784833.3784923","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 11th International Conference on Communication and Information Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7280616164207458,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2144098589","https://openalex.org/W2148913232","https://openalex.org/W2149600645","https://openalex.org/W2606697812","https://openalex.org/W2743678626","https://openalex.org/W2750674396","https://openalex.org/W2753952929","https://openalex.org/W2772317693","https://openalex.org/W4308085832","https://openalex.org/W4320015870","https://openalex.org/W4393188156","https://openalex.org/W4400526177"],"related_works":[],"abstract_inverted_index":{"In":[0],"Non-Terrestrial":[1],"Networks":[2],"(NTN),":[3],"efficiently":[4],"discriminating":[5],"the":[6,25,42,83,112,137],"priority":[7],"of":[8,28,47,118],"multi-source":[9],"heterogeneous":[10],"data":[11,38,85],"from":[12,82],"aerial":[13],"nodes":[14],"is":[15,103],"a":[16,56,66,87,99,115,123],"core":[17],"challenge":[18],"for":[19,157],"optimizing":[20],"link":[21],"resources":[22],"and":[23,40,77,130,149],"ensuring":[24],"communication":[26],"quality":[27],"critical":[29],"tasks.":[30],"Existing":[31],"methods":[32],"show":[33,110],"deficiencies":[34],"in":[35,161],"adapting":[36],"to":[37,120],"heterogeneity":[39],"meeting":[41],"low-power,":[43],"low-latency":[44],"deployment":[45,134],"constraints":[46],"airborne":[48],"platforms.":[49],"To":[50,95],"address":[51],"this,":[52],"this":[53],"paper":[54],"proposes":[55],"lightweight":[57],"intelligent":[58],"task":[59],"classification":[60,116],"model.":[61],"The":[62],"model":[63,106,113],"innovatively":[64],"uses":[65],"unified":[67],"byte":[68],"stream":[69],"as":[70],"input,":[71],"avoiding":[72],"complex":[73],"manual":[74],"feature":[75],"engineering,":[76],"directly":[78],"learns":[79],"discriminative":[80],"features":[81],"raw":[84],"through":[86],"structurally":[88],"simple":[89],"one-dimensional":[90],"convolutional":[91],"neural":[92],"network":[93],"(1D-CNN).":[94],"emphasize":[96],"high-priority":[97],"tasks,":[98],"weighted":[100],"loss":[101],"function":[102],"introduced":[104],"during":[105],"training.":[107],"Experimental":[108],"results":[109],"that":[111],"achieves":[114],"accuracy":[117],"up":[119],"99.78%":[121],"on":[122,136],"comprehensive":[124],"dataset":[125],"including":[126],"text,":[127],"multi-compression-level":[128],"images,":[129],"videos.":[131],"More":[132],"importantly,":[133],"tests":[135],"RK3588":[138],"embedded":[139],"platform":[140],"have":[141],"verified":[142],"its":[143,153],"excellent":[144],"performance":[145],"with":[146],"strong":[147],"throughput":[148],"low":[150],"latency,":[151],"highlighting":[152],"substantial":[154],"practical":[155],"value":[156],"real-world":[158],"engineering":[159],"applications":[160],"NTN":[162],"scenarios.":[163]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-02-03T00:00:00"}
