{"id":"https://openalex.org/W7138077148","doi":"https://doi.org/10.48550/arxiv.2603.14132","title":"DualSwinFusionSeg: Multimodal Martian Landslide Segmentation via Dual Swin Transformer with Multi-Scale Fusion and UNet++","display_name":"DualSwinFusionSeg: Multimodal Martian Landslide Segmentation via Dual Swin Transformer with Multi-Scale Fusion and UNet++","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138077148","doi":"https://doi.org/10.48550/arxiv.2603.14132"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.14132","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.14132","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.2603.14132","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129721292","display_name":"Shahriar Kabir","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kabir, Shahriar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129680051","display_name":"Abdullah Muhammed Amimul Ehsan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ehsan, Abdullah Muhammed Amimul","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129648569","display_name":"Istiak Ahmmed Rifti","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rifti, Istiak Ahmmed","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129726305","display_name":"Md Kaykobad Reza","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Reza, Md Kaykobad","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"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/T10406","display_name":"Planetary Science and Exploration","score":0.9836000204086304,"subfield":{"id":"https://openalex.org/subfields/3103","display_name":"Astronomy and Astrophysics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10406","display_name":"Planetary Science and Exploration","score":0.9836000204086304,"subfield":{"id":"https://openalex.org/subfields/3103","display_name":"Astronomy and Astrophysics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.0008999999845400453,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.0006000000284984708,"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/segmentation","display_name":"Segmentation","score":0.5727999806404114},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.4684000015258789},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.45989999175071716},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4189999997615814},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41600000858306885},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.41359999775886536},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.3695000112056732},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.35760000348091125}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.72079998254776},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6255000233650208},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5727999806404114},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5230000019073486},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.4684000015258789},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.45989999175071716},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4246000051498413},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4189999997615814},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41600000858306885},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.41359999775886536},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.3695000112056732},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.35760000348091125},{"id":"https://openalex.org/C181843262","wikidata":"https://www.wikidata.org/wiki/Q640492","display_name":"Digital elevation model","level":2,"score":0.3303999900817871},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.3222000002861023},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.2964000105857849},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.2856000065803528},{"id":"https://openalex.org/C161840515","wikidata":"https://www.wikidata.org/wiki/Q186131","display_name":"Terrain","level":2,"score":0.27959999442100525},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.26840001344680786},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.2671000063419342},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.25859999656677246},{"id":"https://openalex.org/C78201319","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grayscale","level":3,"score":0.2578999996185303},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.2565000057220459}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.14132","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.14132","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.2603.14132","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.14132","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Automated":[0],"segmentation":[1,86,179],"of":[2,37,45],"Martian":[3],"landslides,":[4],"particularly":[5],"in":[6,72],"tectonically":[7],"active":[8],"regions":[9],"such":[10,56],"as":[11,57],"Valles":[12],"Marineris,is":[13],"important":[14],"for":[15,209],"planetary":[16,28,211],"geology,":[17],"hazard":[18],"assessment,":[19],"and":[20,41,65,74,93,111,130,156,174,191,198],"future":[21],"robotic":[22],"exploration.":[23],"However,":[24],"detecting":[25],"landslides":[26],"from":[27,121,164],"imagery":[29,52],"is":[30],"challenging":[31],"due":[32],"to":[33,107,141],"the":[34,42,122,161,165,195,202],"heterogeneous":[35],"nature":[36],"available":[38],"sensing":[39],"modalities":[40],"limited":[43,182],"number":[44],"labeled":[46],"samples.":[47],"Each":[48],"observation":[49],"combines":[50],"RGB":[51,110],"with":[53,136],"geophysical":[54,113],"measurements":[55],"digital":[58],"elevation":[59],"models,":[60],"slope":[61],"maps,":[62],"thermal":[63],"inertia,":[64],"contextual":[66],"grayscale":[67],"imagery,":[68],"which":[69],"differ":[70],"significantly":[71],"resolution":[73],"statistical":[75],"properties.":[76],"To":[77],"address":[78],"these":[79],"challenges,":[80],"we":[81],"propose":[82],"DualSwinFusionSeg,":[83],"a":[84,133],"multimodal":[85,210],"architecture":[87],"that":[88,171],"separates":[89],"modality-specific":[90,172],"feature":[91,117],"extraction":[92],"performs":[94],"multi-scale":[95],"cross-modal":[96],"fusion.":[97],"The":[98,185],"model":[99,187],"employs":[100],"two":[101,123],"parallel":[102],"Swin":[103],"Transformer":[104],"V2":[105],"encoders":[106,173],"independently":[108],"process":[109],"auxiliary":[112],"inputs,":[114],"producing":[115],"hierarchical":[116],"representations.":[118],"Corresponding":[119],"features":[120],"streams":[124],"are":[125],"fused":[126],"at":[127],"multiple":[128],"scales":[129],"decoded":[131],"using":[132],"UNet++":[134],"decoder":[135,154],"dense":[137],"nested":[138],"skip":[139],"connections":[140],"preserve":[142],"fine":[143],"boundary":[144],"details.":[145],"Extensive":[146],"ablation":[147],"studies":[148],"evaluate":[149],"modality":[150],"contributions,":[151],"loss":[152],"functions,":[153],"architectures,":[155],"fusion":[157,177],"strategies.":[158],"Experiments":[159],"on":[160,194,201],"MMLSv2":[162],"dataset":[163],"PBVS":[166],"2026":[167],"Mars-LS":[168],"Challenge":[169],"show":[170],"simple":[175],"concatenation-based":[176],"improve":[178],"accuracy":[180],"under":[181],"training":[183],"data.":[184],"final":[186],"achieves":[188],"0.867":[189],"mIoU":[190,200],"0.905":[192],"F1":[193],"development":[196],"benchmark":[197],"0.783":[199],"held-out":[203],"test":[204],"set,":[205],"demonstrating":[206],"strong":[207],"performance":[208],"surface":[212],"segmentation.":[213]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-18T00:00:00"}