{"id":"https://openalex.org/W7130696817","doi":"https://doi.org/10.1109/lsp.2026.3666752","title":"Structural Priming With High-Frequency Gradient for Mamba in UAV Object Detection","display_name":"Structural Priming With High-Frequency Gradient for Mamba in UAV Object Detection","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7130696817","doi":"https://doi.org/10.1109/lsp.2026.3666752"},"language":null,"primary_location":{"id":"doi:10.1109/lsp.2026.3666752","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2026.3666752","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","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/A5070016538","display_name":"Chaolan Dai","orcid":null},"institutions":[{"id":"https://openalex.org/I118612203","display_name":"Hunan Police Academy","ror":"https://ror.org/02gh10772","country_code":"CN","type":"education","lineage":["https://openalex.org/I118612203"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chaolan Dai","raw_affiliation_strings":["Hunan Police Academy, Changsha, China"],"raw_orcid":"https://orcid.org/0009-0004-2148-9244","affiliations":[{"raw_affiliation_string":"Hunan Police Academy, Changsha, China","institution_ids":["https://openalex.org/I118612203"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017867880","display_name":"Xiaofeng Feng","orcid":"https://orcid.org/0000-0002-9473-2848"},"institutions":[{"id":"https://openalex.org/I118612203","display_name":"Hunan Police Academy","ror":"https://ror.org/02gh10772","country_code":"CN","type":"education","lineage":["https://openalex.org/I118612203"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaofeng Feng","raw_affiliation_strings":["Hunan Police Academy, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hunan Police Academy, Changsha, China","institution_ids":["https://openalex.org/I118612203"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I118612203"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1676204,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":null,"first_page":"1131","last_page":"1135"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.8950999975204468,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.8950999975204468,"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/T11133","display_name":"UAV Applications and Optimization","score":0.020600000396370888,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.013500000350177288,"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/object-detection","display_name":"Object detection","score":0.775600016117096},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5679000020027161},{"id":"https://openalex.org/keywords/blob-detection","display_name":"Blob detection","score":0.5478000044822693},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5109000205993652},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5099999904632568},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45829999446868896},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.43720000982284546},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4230000078678131},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.34860000014305115}],"concepts":[{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.775600016117096},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7741000056266785},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7034000158309937},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.695900022983551},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5679000020027161},{"id":"https://openalex.org/C29168087","wikidata":"https://www.wikidata.org/wiki/Q1026711","display_name":"Blob detection","level":5,"score":0.5478000044822693},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5109000205993652},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5099999904632568},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45829999446868896},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.43720000982284546},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4230000078678131},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.34860000014305115},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.34450000524520874},{"id":"https://openalex.org/C81444415","wikidata":"https://www.wikidata.org/wiki/Q7243535","display_name":"Priming (agriculture)","level":3,"score":0.313400000333786},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.30309998989105225},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.2994999885559082},{"id":"https://openalex.org/C2779769447","wikidata":"https://www.wikidata.org/wiki/Q3813641","display_name":"Foreground detection","level":4,"score":0.29319998621940613},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2867000102996826},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.2849999964237213},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2842000126838684},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2768000066280365},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.272599995136261},{"id":"https://openalex.org/C76935873","wikidata":"https://www.wikidata.org/wiki/Q209121","display_name":"Image sensor","level":2,"score":0.2718999981880188},{"id":"https://openalex.org/C145804949","wikidata":"https://www.wikidata.org/wiki/Q478123","display_name":"Situation awareness","level":2,"score":0.26969999074935913},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.2567000091075897},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.25519999861717224},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.25440001487731934},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2540999948978424}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2026.3666752","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2026.3666752","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.822887659072876,"display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G7111484572","display_name":"\u57fa\u4e8eTransformer\u4e0e\u751f\u7269\u529b\u5b66\u7279\u5f81\u7684\u8de8\u6a21\u6001\u7535\u5b50\u7b14\u8ff9\u771f\u4f2a\u9274\u522b\u7814\u7a76","funder_award_id":"2026JJ81162","funder_id":"https://openalex.org/F4320322843","funder_display_name":"Natural Science Foundation of\u00a0Hunan Province"}],"funders":[{"id":"https://openalex.org/F4320322843","display_name":"Natural Science Foundation of\u00a0Hunan Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Low-altitude":[0],"unmanned":[1],"aerial":[2,45],"vehicles":[3],"(UAVs)":[4],"are":[5,63,124],"increasingly":[6],"employed":[7],"in":[8,24,195,212],"surveillance":[9],"and":[10,19,41,60,92,107,115,120,143,175,199,205],"monitoring":[11,211],"tasks":[12],"such":[13,57],"as":[14,58],"perimeter":[15],"inspection,":[16],"urban":[17],"patrol,":[18],"emergency":[20],"response.":[21],"Object":[22],"detection":[23,86,113,197],"these":[25],"scenarios":[26],"is":[27,156],"highly":[28],"challenging":[29,185],"due":[30],"to":[31,171],"the":[32,134],"small":[33],"size":[34],"of":[35],"targets,":[36],"frequent":[37],"occlusions,":[38],"cluttered":[39],"backgrounds,":[40],"blurred":[42],"boundaries":[43],"from":[44],"viewpoints.":[46],"Existing":[47],"detectors":[48,194],"primarily":[49],"emphasize":[50],"semantic":[51,91,119],"abstraction,":[52],"while":[53],"overlooking":[54],"structural":[55,93,122],"cues":[56],"edges":[59],"contours,":[61],"which":[62],"often":[64],"critical":[65],"for":[66,82,208],"precise":[67],"localization.":[68],"To":[69],"address":[70],"this":[71],"gap,":[72],"we":[73],"propose":[74],"SPHMamba":[75,190],"(Structural":[76],"Priming":[77],"with":[78,166,179],"High":[79],"Frequency":[80],"Gradient":[81],"Mamba),":[83],"a":[84,104,108,128,148,160,167],"boundary-aware":[85],"framework":[87],"that":[88,189],"explicitly":[89],"integrates":[90],"information.":[94],"A":[95],"dual-stream":[96],"representation":[97,155],"module":[98],"first":[99],"extracts":[100],"complementary":[101],"features":[102],"through":[103],"Semantic":[105],"Stream":[106],"Structural":[109,168],"Stream,":[110],"yielding":[111],"both":[112,196],"predictions":[114],"modulation":[116],"matrices.":[117],"These":[118],"high-frequency":[121],"priors":[123],"subsequently":[125],"injected":[126],"into":[127],"Structure-Primed":[129],"Mamba":[130],"Block":[131],"(SPMB),":[132],"where":[133],"selective":[135],"scan":[136],"mechanism":[137],"adaptively":[138],"propa":[139],"gates":[140],"boundary-sensitive":[141],"information":[142],"suppresses":[144],"background":[145],"noise,":[146],"producing":[147],"High-Probability":[149],"Correction":[150],"Matrix":[151],"(HPCM).":[152],"The":[153],"refined":[154],"then":[157],"incorporated":[158],"by":[159],"Boundary":[161],"Refinement":[162],"Module":[163],"(BRM),":[164],"optimized":[165],"Alignment":[169],"Loss,":[170],"enhance":[172],"localization":[173],"precision":[174],"achieve":[176],"tighter":[177],"alignment":[178],"object":[180],"contours.":[181],"Extensive":[182],"experiments":[183],"on":[184],"UAV":[186],"benchmarks":[187],"demonstrate":[188],"consistently":[191],"outperforms":[192],"state-of-the-art":[193],"accuracy":[198],"boundary":[200],"localization,":[201],"providing":[202],"an":[203],"efficient":[204],"generalizable":[206],"solution":[207],"intelligent":[209],"UAV-based":[210],"complex":[213],"environments.":[214]},"counts_by_year":[],"updated_date":"2026-07-13T07:31:44.756512","created_date":"2026-02-21T00:00:00"}
