{"id":"https://openalex.org/W7140165009","doi":"https://doi.org/10.48550/arxiv.2603.21192","title":"DSCSNet: A Dynamic Sparse Compression Sensing Network for Closely-Spaced Infrared Small Target Unmixing","display_name":"DSCSNet: A Dynamic Sparse Compression Sensing Network for Closely-Spaced Infrared Small Target Unmixing","publication_year":2026,"publication_date":"2026-03-22","ids":{"openalex":"https://openalex.org/W7140165009","doi":"https://doi.org/10.48550/arxiv.2603.21192"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.21192","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.21192","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.21192","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Tang, Zhiyang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Tang, Zhiyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Zhu, Yiming","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Yiming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Huang, Ruimin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Ruimin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Yang, Meng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Meng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Ma, Yong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Yong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Huang, Jun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Jun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Fan, Fan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fan, Fan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":0.5895000100135803,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.5895000100135803,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.05220000073313713,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T11517","display_name":"Advanced optical system design","score":0.03359999880194664,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/compressed-sensing","display_name":"Compressed sensing","score":0.5460000038146973},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.5393000245094299},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.46059998869895935},{"id":"https://openalex.org/keywords/iterative-method","display_name":"Iterative method","score":0.45019999146461487},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4205000102519989},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.40369999408721924},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3968999981880188},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.396699994802475},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.3903999924659729}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7098000049591064},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.5460000038146973},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.5393000245094299},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5385000109672546},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.46059998869895935},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.45019999146461487},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4205000102519989},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41290000081062317},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.40369999408721924},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3968999981880188},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.396699994802475},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.3903999924659729},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3880000114440918},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.375900000333786},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.36000001430511475},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.3393999934196472},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.32499998807907104},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.30720001459121704},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.30169999599456787},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.2987000048160553},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.29660001397132874},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.29120001196861267},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.2892000079154968},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.2888000011444092},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.27900001406669617},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.27570000290870667},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.265500009059906},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.257099986076355},{"id":"https://openalex.org/C158355884","wikidata":"https://www.wikidata.org/wiki/Q11388","display_name":"Infrared","level":2,"score":0.25600001215934753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.21192","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.21192","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.21192","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.21192","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.5739171504974365}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Due":[0],"to":[1,30,55,117],"the":[2,32,57,65,91,110,119,127,143,149,153,157,167,174,190,202],"limitations":[3],"of":[4,39,61,69,95,115,131,171,177],"optical":[5],"lens":[6],"focal":[7],"length":[8],"and":[9,36,64,185,193,219],"detector":[10],"resolution,":[11],"distant":[12],"clustered":[13],"infrared":[14,197,204],"small":[15,132],"targets":[16,41],"often":[17],"appear":[18],"as":[19,217],"mixed":[20],"spots.":[21],"The":[22],"Close":[23],"Small":[24],"Object":[25],"Unmixing":[26],"(CSOU)":[27],"task":[28],"aims":[29],"recover":[31],"number,":[33],"sub-pixel":[34,220],"positions,":[35],"radiant":[37],"intensities":[38],"individual":[40],"from":[42,156],"these":[43],"spots,":[44],"which":[45,124,146],"is":[46],"a":[47,79,86,104,137],"highly":[48],"ill-posed":[49],"inverse":[50],"problem.":[51],"Existing":[52],"methods":[53,212],"struggle":[54],"balance":[56],"rigorous":[58],"sparsity":[59,107,183],"guarantees":[60],"model-driven":[62],"approaches":[63],"dynamic":[66,139],"scene":[67,186],"adaptability":[68],"data-driven":[70],"methods.":[71],"To":[72],"address":[73],"this":[74,76],"dilemma,":[75],"paper":[77],"proposes":[78],"Dynamic":[80],"Sparse":[81],"Compressed":[82],"Sensing":[83],"Network":[84],"(DSCSNet),":[85],"deep-unfolded":[87],"network":[88],"that":[89,208],"couples":[90],"Alternating":[92],"Direction":[93],"Method":[94],"Multipliers":[96],"(ADMM)":[97],"with":[98],"learnable":[99],"parameters.":[100],"Specifically,":[101],"we":[102],"embed":[103],"strict":[105],"$\\ell_1$-norm":[106],"constraint":[108],"into":[109,142],"auxiliary":[111],"variable":[112],"update":[113],"step":[114],"ADMM":[116],"replace":[118],"traditional":[120],"$\\ell_2$-norm":[121],"smoothness-promoting":[122],"terms,":[123],"effectively":[125],"preserves":[126],"discrete":[128],"energy":[129],"peaks":[130],"targets.":[133],"We":[134],"also":[135],"integrate":[136],"self-attention-based":[138],"thresholding":[140],"mechanism":[141],"reconstruction":[144],"stage,":[145],"adaptively":[147],"adjusts":[148],"sparsification":[150],"intensity":[151],"using":[152],"sparsity-enhanced":[154],"information":[155],"iterative":[158,169],"process.":[159],"These":[160],"modules":[161],"are":[162],"jointly":[163],"optimized":[164],"end-to-end":[165],"across":[166],"three":[168],"steps":[170],"ADMM.":[172],"Retaining":[173],"physical":[175],"logic":[176],"compressed":[178],"sensing,":[179],"DSCSNet":[180,209],"achieves":[181],"robust":[182],"induction":[184],"adaptability,":[187],"thus":[188],"enhancing":[189],"unmixing":[191],"accuracy":[192],"generalization":[194],"in":[195,213],"complex":[196],"scenarios.":[198],"Extensive":[199],"experiments":[200],"on":[201],"synthetic":[203],"dataset":[205],"CSIST-100K":[206],"demonstrate":[207],"outperforms":[210],"state-of-the-art":[211],"key":[214],"metrics":[215],"such":[216],"CSO-mAP":[218],"localization":[221],"error.":[222]},"counts_by_year":[],"updated_date":"2026-04-25T08:17:42.794288","created_date":"2026-03-25T00:00:00"}