{"id":"https://openalex.org/W7213339458","doi":"https://doi.org/10.48550/arxiv.2609.13332","title":"Global-Local Contextual Progressive Expansion Network for Martian Landslide Segmentation in Multimodal Remote Sensing Imagery","display_name":"Global-Local Contextual Progressive Expansion Network for Martian Landslide Segmentation in Multimodal Remote Sensing Imagery","publication_year":2026,"publication_date":"2026-09-11","ids":{"openalex":"https://openalex.org/W7213339458","doi":"https://doi.org/10.48550/arxiv.2609.13332"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2609.13332","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.13332","pdf_url":"https://arxiv.org/pdf/2609.13332","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2609.13332","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000019015","display_name":"Leo Ramos","orcid":"https://orcid.org/0000-0001-7107-7943","observed_orcids":["https://orcid.org/0000-0001-7107-7943"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ramos, Leo Thomas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5151845079","display_name":"Sidike Paheding","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Paheding, Sidike","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070748079","display_name":"Abel A. Reyes","orcid":"https://orcid.org/0000-0003-0332-8231","observed_orcids":["https://orcid.org/0000-0003-0332-8231"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Reyes-Angulo, Abel A.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064376747","display_name":"Ambujendran Rajaneesh","orcid":"https://orcid.org/0000-0003-0732-5046","observed_orcids":["https://orcid.org/0000-0003-0732-5046"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"A., Rajaneesh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029634464","display_name":"Kochappi Sathyan Sajinkumar","orcid":"https://orcid.org/0000-0002-6461-8112","observed_orcids":["https://orcid.org/0000-0002-6461-8112"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"S., Sajinkumar K.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002373986","display_name":"Angel Domingo Sappa","orcid":"https://orcid.org/0000-0003-2468-0031","observed_orcids":["https://orcid.org/0000-0003-2468-0031"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sappa, Angel D.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5006970579","display_name":"Thomas Oommen","orcid":"https://orcid.org/0000-0002-1024-3474","observed_orcids":["https://orcid.org/0000-0002-1024-3474"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Oommen, Thomas","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":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/T10535","display_name":"Landslides and related hazards","score":0.3617999851703644,"subfield":{"id":"https://openalex.org/subfields/2308","display_name":"Management, Monitoring, Policy and Law"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10535","display_name":"Landslides and related hazards","score":0.3617999851703644,"subfield":{"id":"https://openalex.org/subfields/2308","display_name":"Management, Monitoring, Policy and Law"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.32910001277923584,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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":0.2295999974012375,"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/martian-landslides","display_name":"Martian landslides","score":0.9599999785423279},{"id":"https://openalex.org/keywords/landslide-segmentation","display_name":"landslide segmentation","score":0.9480000138282776},{"id":"https://openalex.org/keywords/martian-surface-processes","display_name":"Mars surface processes","score":0.7310000061988831},{"id":"https://openalex.org/keywords/planetary-remote-sensing","display_name":"planetary remote sensing","score":0.8180000185966492}],"concepts":[{"id":"https://openalex.org/C186295008","wikidata":"https://www.wikidata.org/wiki/Q167903","display_name":"Landslide","level":2,"score":0.7462999820709229},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7092000246047974},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6470000147819519},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5590000152587891},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5432999730110168},{"id":"https://openalex.org/C2778600265","wikidata":"https://www.wikidata.org/wiki/Q913850","display_name":"Martian","level":3,"score":0.49619999527931213},{"id":"https://openalex.org/C83260615","wikidata":"https://www.wikidata.org/wiki/Q6773121","display_name":"Mars Exploration Program","level":2,"score":0.4431000053882599},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.42829999327659607},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4180000126361847},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3801000118255615},{"id":"https://openalex.org/C2776219924","wikidata":"https://www.wikidata.org/wiki/Q6774740","display_name":"Martian surface","level":4,"score":0.34630000591278076},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3352000117301941},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.33009999990463257},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.32030001282691956},{"id":"https://openalex.org/C2778102629","wikidata":"https://www.wikidata.org/wiki/Q725252","display_name":"Satellite imagery","level":2,"score":0.3061000108718872},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.29649999737739563},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.2879999876022339},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.2549999952316284},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.25270000100135803}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2609.13332","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.13332","pdf_url":"https://arxiv.org/pdf/2609.13332","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2609.13332","doi":"https://doi.org/10.48550/arxiv.2609.13332","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2609.13332","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2609.13332","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.13332","pdf_url":"https://arxiv.org/pdf/2609.13332","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4385800710","https://openalex.org/W4394596929","https://openalex.org/W7196991420","https://openalex.org/W4416726097","https://openalex.org/W7128487674","https://openalex.org/W7138077148","https://openalex.org/W7135187669","https://openalex.org/W7116896289","https://openalex.org/W4411280353","https://openalex.org/W4394842018"],"abstract_inverted_index":{"Automated":[0],"landslide":[1,33,68,133,142,163],"segmentation":[2,69,77,185],"on":[3,136,154],"Mars":[4],"is":[5,35,86],"one":[6],"of":[7,62,74,82],"the":[8,60,80,87,119,148],"important":[9],"tasks":[10],"for":[11,130,206],"understanding":[12],"its":[13],"surface":[14],"processes,":[15],"and":[16,45,51,126,168,174,183,197,201],"all":[17],"will":[18,211],"aid":[19],"in":[20,96,203],"future":[21],"space":[22],"exploration.":[23],"However,":[24],"it":[25],"remains":[26],"a":[27,93,103,138,169,194],"relatively":[28],"underexplored":[29],"open":[30],"challenge":[31],"because":[32],"morphology":[34],"highly":[36],"variable,":[37],"foreground":[38,166],"regions":[39],"are":[40],"often":[41],"sparse":[42],"or":[43],"irregular,":[44],"orbital":[46],"observations":[47],"combine":[48],"heterogeneous":[49],"spectral":[50],"topographic":[52],"cues.":[53],"In":[54],"this":[55,57,85,97,188],"context,":[56],"work":[58],"investigates":[59],"capability":[61],"deep":[63,204],"learning":[64,205],"to":[65,90,121,192],"address":[66],"Martian":[67,141],"through":[70],"an":[71],"extensive":[72],"assessment":[73],"modern":[75],"neural":[76],"models.":[78,186],"To":[79],"best":[81,149],"our":[83],"knowledge,":[84],"first":[88],"study":[89],"provide":[91,193],"such":[92],"comprehensive":[94],"exploration":[95],"domain.":[98],"We":[99],"further":[100,199],"propose":[101],"TransCPLES,":[102],"U-shaped":[104],"network":[105],"that":[106,145],"couples":[107],"Contextual":[108],"Progressive":[109],"Layer":[110],"Expansion":[111],"feature":[112],"extraction":[113],"with":[114,158,178],"Transformer-based":[115,184],"contextual":[116],"reasoning,":[117],"enabling":[118],"model":[120],"capture":[122],"local":[123],"geomorphic":[124],"patterns":[125],"broader":[127],"spatial":[128],"dependencies":[129],"more":[131],"reliable":[132],"delineation.":[134],"Experiments":[135],"MMLSv2,":[137],"seven-band":[139],"multimodal":[140],"dataset,":[143],"show":[144],"TransCPLES":[146],"achieves":[147],"overall":[150],"performance":[151],"when":[152],"evaluated":[153],"geographically":[155],"distinct":[156],"samples,":[157],"consistent":[159],"delineation":[160],"across":[161],"different":[162],"extents,":[164],"stable":[165],"discrimination,":[167],"favorable":[170],"balance":[171],"between":[172],"accuracy":[173],"computational":[175],"cost":[176],"compared":[177],"several":[179],"state-of-the-art":[180],"convolutional,":[181],"attention-based,":[182],"With":[187],"work,":[189],"we":[190],"hope":[191],"useful":[195],"reference":[196],"encourage":[198],"research":[200],"development":[202],"planetary":[207],"remote":[208],"sensing.":[209],"Code":[210],"be":[212],"available":[213],"after":[214],"publication.":[215]},"counts_by_year":[],"updated_date":"2026-10-28T10:33:24.094632","created_date":"2026-09-16T00:00:00"}
