{"id":"https://openalex.org/W7133293807","doi":"https://doi.org/10.48550/arxiv.2603.01361","title":"MixerCSeg: An Efficient Mixer Architecture for Crack Segmentation via Decoupled Mamba Attention","display_name":"MixerCSeg: An Efficient Mixer Architecture for Crack Segmentation via Decoupled Mamba Attention","publication_year":2026,"publication_date":"2026-03-02","ids":{"openalex":"https://openalex.org/W7133293807","doi":"https://doi.org/10.48550/arxiv.2603.01361"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.01361","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01361","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.01361","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5127982130","display_name":"Zilong Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Zilong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127917959","display_name":"Zhengming Ding","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ding, Zhengming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063827622","display_name":"Pei Xing Niu","orcid":"https://orcid.org/0000-0002-2661-1518"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Niu, Pei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127952256","display_name":"Wenhao Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Wenhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5127885135","display_name":"Feng Guo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Feng","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":null,"has_fulltext":false,"cited_by_count":1,"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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.8956000208854675,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.8956000208854675,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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":0.05889999866485596,"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":0.00419999985024333,"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/segmentation","display_name":"Segmentation","score":0.6310999989509583},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5511999726295471},{"id":"https://openalex.org/keywords/locality","display_name":"Locality","score":0.5421000123023987},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5073000192642212},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5055999755859375},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5034000277519226},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.48899999260902405},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4821999967098236}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6940000057220459},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6310999989509583},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5511999726295471},{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.5421000123023987},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5073000192642212},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5055999755859375},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5034000277519226},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.48899999260902405},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4821999967098236},{"id":"https://openalex.org/C3826847","wikidata":"https://www.wikidata.org/wiki/Q188768","display_name":"FLOPS","level":2,"score":0.47850000858306885},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4426000118255615},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.40299999713897705},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4011000096797943},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.3741999864578247},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.3711000084877014},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3587000072002411},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3549000024795532},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.3522999882698059},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3490000069141388},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33500000834465027},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.32739999890327454},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.31150001287460327},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.29829999804496765},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.2955999970436096},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2856000065803528},{"id":"https://openalex.org/C27602214","wikidata":"https://www.wikidata.org/wiki/Q1868547","display_name":"Locality of reference","level":3,"score":0.2782999873161316},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.2757999897003174},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.2648000121116638}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.01361","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01361","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.01361","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01361","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.7211211919784546,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Feature":[0],"encoders":[1],"play":[2],"a":[3,51,56,80,116,122],"key":[4],"role":[5],"in":[6,40],"pixel-level":[7],"crack":[8,43,134,161],"segmentation":[9,162],"by":[10],"shaping":[11],"the":[12,31,84,89],"representation":[13],"of":[14,30,59,86],"fine":[15],"textures":[16],"and":[17,23,73,106,121,174,181],"thin":[18],"structures.":[19],"Existing":[20],"CNN-,":[21],"Transformer-,":[22],"Mamba-based":[24],"models":[25],"each":[26],"capture":[27,70],"only":[28,171],"part":[29],"required":[32],"spatial":[33,117],"or":[34],"structural":[35,112],"information,":[36],"leaving":[37],"clear":[38],"gaps":[39],"modeling":[41],"complex":[42],"patterns.":[44],"To":[45,109],"address":[46],"this,":[47],"we":[48,114],"present":[49],"MixerCSeg,":[50],"mixer":[52],"architecture":[53],"designed":[54],"like":[55],"coordinated":[57],"team":[58],"specialists,":[60],"where":[61],"CNN-like":[62],"pathways":[63,100],"focus":[64],"on":[65,159],"local":[66],"textures,":[67],"Transformer-style":[68],"paths":[69],"global":[71,107],"dependencies,":[72],"Mamba-inspired":[74],"flows":[75],"model":[76],"sequential":[77],"context":[78],"within":[79],"single":[81],"encoder.":[82],"At":[83],"core":[85],"MixerCSeg":[87,166],"is":[88,147,187],"TransMixer,":[90],"which":[91],"explores":[92],"Mamba's":[93],"latent":[94],"attention":[95],"behavior":[96],"while":[97],"establishing":[98],"dedicated":[99],"that":[101,128,165],"naturally":[102],"express":[103],"both":[104,179],"locality":[105],"awareness.":[108],"further":[110],"enhance":[111],"fidelity,":[113],"introduce":[115],"block":[118],"processing":[119],"strategy":[120],"Direction-guided":[123],"Edge":[124],"Gated":[125],"Convolution":[126],"(DEGConv)":[127],"strengthens":[129],"edge":[130],"sensitivity":[131],"under":[132],"irregular":[133],"geometries":[135],"with":[136,170],"minimal":[137],"computational":[138],"overhead.":[139],"A":[140],"Spatial":[141],"Refinement":[142],"Multi-Level":[143],"Fusion":[144],"(SRF)":[145],"module":[146],"then":[148],"employed":[149],"to":[150],"refine":[151],"multi-scale":[152],"details":[153],"without":[154],"increasing":[155],"complexity.":[156],"Extensive":[157],"experiments":[158],"multiple":[160],"benchmarks":[163],"show":[164],"achieves":[167],"state-of-the-art":[168],"performance":[169],"2.05":[172],"GFLOPs":[173],"2.54":[175],"M":[176],"parameters,":[177],"demonstrating":[178],"efficiency":[180],"strong":[182],"representational":[183],"capability.":[184],"The":[185],"code":[186],"available":[188],"at":[189],"https://github.com/spiderforest/MixerCSeg.":[190]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-04T00:00:00"}
