{"id":"https://openalex.org/W7204785673","doi":"https://doi.org/10.3390/rs18172905","title":"Preprocessing Mismatch and Input Normalisation in Transferring a Multispectral Foundation Model to Marine Surface Segmentation","display_name":"Preprocessing Mismatch and Input Normalisation in Transferring a Multispectral Foundation Model to Marine Surface Segmentation","publication_year":2026,"publication_date":"2026-08-29","ids":{"openalex":"https://openalex.org/W7204785673","doi":"https://doi.org/10.3390/rs18172905"},"language":"en","primary_location":{"id":"doi:10.3390/rs18172905","doi":"https://doi.org/10.3390/rs18172905","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs18172905","pdf_url":null,"source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","jufo-1","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/rs18172905","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5119214710","display_name":"Christos G. E. Anagnostopoulos","orcid":"https://orcid.org/0009-0006-9839-4870","observed_orcids":["https://orcid.org/0009-0006-9839-4870"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Christos G. E. Anagnostopoulos","raw_affiliation_strings":["CDXi Solutions P.C., 54621 Thessaloniki, Greece"],"raw_orcid":"https://orcid.org/0009-0006-9839-4870","affiliations":[{"raw_affiliation_string":"CDXi Solutions P.C., 54621 Thessaloniki, Greece","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029998399","display_name":"Konstantinos Vlachos","orcid":"https://orcid.org/0000-0001-7979-367X","observed_orcids":["https://orcid.org/0000-0001-7979-367X"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Konstantinos Vlachos","raw_affiliation_strings":["CDXi Solutions P.C., 54621 Thessaloniki, Greece"],"raw_orcid":"https://orcid.org/0000-0001-7979-367X","affiliations":[{"raw_affiliation_string":"CDXi Solutions P.C., 54621 Thessaloniki, Greece","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078232784","display_name":"Anastasia Moumtzidou","orcid":"https://orcid.org/0000-0001-7615-8400","observed_orcids":["https://orcid.org/0000-0001-7615-8400"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Anastasia Moumtzidou","raw_affiliation_strings":["CDXi Solutions P.C., 54621 Thessaloniki, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CDXi Solutions P.C., 54621 Thessaloniki, Greece","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008331264","display_name":"Ilias Gialampoukidis","orcid":"https://orcid.org/0000-0002-5234-9795","observed_orcids":["https://orcid.org/0000-0002-5234-9795"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ilias Gialampoukidis","raw_affiliation_strings":["CDXi Solutions P.C., 54621 Thessaloniki, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CDXi Solutions P.C., 54621 Thessaloniki, Greece","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065313479","display_name":"Stefanos Vrochidis","orcid":"https://orcid.org/0000-0002-2505-9178","observed_orcids":["https://orcid.org/0000-0002-2505-9178"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Stefanos Vrochidis","raw_affiliation_strings":["CDXi Solutions P.C., 54621 Thessaloniki, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CDXi Solutions P.C., 54621 Thessaloniki, Greece","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008246457","display_name":"Ariane Mueting","orcid":"https://orcid.org/0000-0001-5715-1801","observed_orcids":["https://orcid.org/0000-0001-5715-1801"]},"institutions":[{"id":"https://openalex.org/I44377176","display_name":"European Space Research and Technology Centre","ror":"https://ror.org/03h3jqn23","country_code":"NL","type":"government","lineage":["https://openalex.org/I2801994115","https://openalex.org/I44377176"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Ariane M\u00fcting","raw_affiliation_strings":["ESTEC\u2014European Space Research and Technology Centre, Keplerlaan 1, 2200 AG Noordwijk, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ESTEC\u2014European Space Research and Technology Centre, Keplerlaan 1, 2200 AG Noordwijk, The Netherlands","institution_ids":["https://openalex.org/I44377176"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138522112","display_name":"Ana Sofia Oliveira","orcid":"https://orcid.org/0009-0001-2431-5141","observed_orcids":["https://orcid.org/0009-0001-2431-5141"]},"institutions":[{"id":"https://openalex.org/I44377176","display_name":"European Space Research and Technology Centre","ror":"https://ror.org/03h3jqn23","country_code":"NL","type":"government","lineage":["https://openalex.org/I2801994115","https://openalex.org/I44377176"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Ana Sofia Oliveira","raw_affiliation_strings":["ESTEC\u2014European Space Research and Technology Centre, Keplerlaan 1, 2200 AG Noordwijk, The Netherlands"],"raw_orcid":"https://orcid.org/0009-0001-2431-5141","affiliations":[{"raw_affiliation_string":"ESTEC\u2014European Space Research and Technology Centre, Keplerlaan 1, 2200 AG Noordwijk, The Netherlands","institution_ids":["https://openalex.org/I44377176"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035868660","display_name":"Dimitris Bliziotis","orcid":"https://orcid.org/0009-0003-4535-0303","observed_orcids":["https://orcid.org/0009-0003-4535-0303"]},"institutions":[{"id":"https://openalex.org/I4210150472","display_name":"Ministry of Digital Governance","ror":"https://ror.org/04n9t5970","country_code":"GR","type":"government","lineage":["https://openalex.org/I4210150472"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Dimitris Bliziotis","raw_affiliation_strings":["Hellenic Space Center, Ministry of Digital Governance, 15342 Agia Paraskevi, Greece"],"raw_orcid":"https://orcid.org/0009-0003-4535-0303","affiliations":[{"raw_affiliation_string":"Hellenic Space Center, Ministry of Digital Governance, 15342 Agia Paraskevi, Greece","institution_ids":["https://openalex.org/I4210150472"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019605722","display_name":"Katerina Kikaki","orcid":"https://orcid.org/0000-0002-2618-3074","observed_orcids":["https://orcid.org/0000-0002-2618-3074"]},"institutions":[{"id":"https://openalex.org/I4210150472","display_name":"Ministry of Digital Governance","ror":"https://ror.org/04n9t5970","country_code":"GR","type":"government","lineage":["https://openalex.org/I4210150472"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Katerina Kikaki","raw_affiliation_strings":["Hellenic Space Center, Ministry of Digital Governance, 15342 Agia Paraskevi, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hellenic Space Center, Ministry of Digital Governance, 15342 Agia Paraskevi, Greece","institution_ids":["https://openalex.org/I4210150472"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5029998399"],"corresponding_institution_ids":[],"apc_list":{"value":2700,"currency":"CHF","value_usd":3258},"apc_paid":{"value":2700,"currency":"CHF","value_usd":3258},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"18","issue":"17","first_page":"2905","last_page":"2905"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.8076000213623047,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.8076000213623047,"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/T12316","display_name":"Oil Spill Detection and Mitigation","score":0.055799998342990875,"subfield":{"id":"https://openalex.org/subfields/2310","display_name":"Pollution"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.052000001072883606,"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/frozen-encoder","display_name":"frozen encoder","score":0.3779999911785126},{"id":"https://openalex.org/keywords/test-time-augmentation","display_name":"test-time augmentation","score":0.7519999742507935},{"id":"https://openalex.org/keywords/exponentially-weighted-moving-average","display_name":"exponential moving average","score":0.6209999918937683},{"id":"https://openalex.org/keywords/sentinel-2","display_name":"Sentinel-2","score":0.4970000088214874},{"id":"https://openalex.org/keywords/atmospheric-correction","display_name":"atmospheric correction","score":0.6380000114440918},{"id":"https://openalex.org/keywords/oil-spill-detection","display_name":"oil spill detection","score":0.6389999985694885}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7398999929428101},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5160999894142151},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.49799999594688416},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.49399998784065247},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.42719998955726624},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4068000018596649},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39800000190734863},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3711000084877014},{"id":"https://openalex.org/C163204269","wikidata":"https://www.wikidata.org/wiki/Q355263","display_name":"Chrominance","level":3,"score":0.3382999897003174},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.33169999718666077},{"id":"https://openalex.org/C2775938548","wikidata":"https://www.wikidata.org/wiki/Q1565182","display_name":"Thematic Mapper","level":3,"score":0.30709999799728394},{"id":"https://openalex.org/C114700698","wikidata":"https://www.wikidata.org/wiki/Q2882278","display_name":"Spectral bands","level":2,"score":0.27900001406669617},{"id":"https://openalex.org/C108597893","wikidata":"https://www.wikidata.org/wiki/Q663650","display_name":"Reflectivity","level":2,"score":0.2773999869823456},{"id":"https://openalex.org/C205203396","wikidata":"https://www.wikidata.org/wiki/Q612143","display_name":"Bilinear interpolation","level":2,"score":0.2750999927520752},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.27000001072883606},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.26489999890327454},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.2646999955177307},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.2639999985694885},{"id":"https://openalex.org/C98083399","wikidata":"https://www.wikidata.org/wiki/Q3246517","display_name":"Underwater","level":2,"score":0.2635999917984009},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.26260000467300415},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/rs18172905","doi":"https://doi.org/10.3390/rs18172905","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs18172905","pdf_url":null,"source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","jufo-1","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:9db92573a042461c95e572ba6c15f018","doi":null,"is_oa":false,"landing_page_url":"https://doaj.org/article/9db92573a042461c95e572ba6c15f018","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 18, Iss 17, p 2905 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/rs18172905","doi":"https://doi.org/10.3390/rs18172905","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs18172905","pdf_url":null,"source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","jufo-1","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1849277567","https://openalex.org/W2188436909","https://openalex.org/W2344328155","https://openalex.org/W2597944323","https://openalex.org/W2782219207","https://openalex.org/W2787159650","https://openalex.org/W2884226222","https://openalex.org/W2889603884","https://openalex.org/W2911964244","https://openalex.org/W2964288524","https://openalex.org/W2988903679","https://openalex.org/W3109296750","https://openalex.org/W3132684617","https://openalex.org/W4205835860","https://openalex.org/W4225747866","https://openalex.org/W4288076010","https://openalex.org/W4312349930","https://openalex.org/W4312804044","https://openalex.org/W4387026640","https://openalex.org/W4392574360","https://openalex.org/W4393906060","https://openalex.org/W4395055639","https://openalex.org/W4402064504","https://openalex.org/W4402667899","https://openalex.org/W4406125612","https://openalex.org/W4414786466","https://openalex.org/W4415623721","https://openalex.org/W4417248811","https://openalex.org/W7133201458"],"related_works":["https://openalex.org/W7135218807","https://openalex.org/W7214765474","https://openalex.org/W7172557698","https://openalex.org/W7203598357","https://openalex.org/W7221496774","https://openalex.org/W7159072712","https://openalex.org/W7162680536","https://openalex.org/W4399344797","https://openalex.org/W7170187620","https://openalex.org/W4403635970"],"abstract_inverted_index":{"Foundation":[0],"models":[1],"for":[2,131,346],"Earth":[3],"observation":[4],"are":[5,85,115,123,241,344],"commonly":[6],"transferred":[7],"to":[8,14,54,190,243,261,309,338,372,392,397],"downstream":[9],"tasks":[10],"without":[11],"explicit":[12],"attention":[13],"the":[15,35,55,75,98,106,110,132,151,159,171,182,186,191,223,267,275,298,303,306,310,314,329,363,373,398,402],"preprocessing":[16,26,113,320],"mismatch":[17,27,145],"between":[18,146,313,401],"pretraining":[19,378],"and":[20,58,71,97,135,148,230,255,273,287,316],"target":[21,212,317,353],"distributions.":[22,318,404],"This":[23],"study":[24],"isolates":[25],"as":[28,105,196,198],"a":[29,40,206,334,347],"controlled":[30],"experimental":[31],"factor":[32],"in":[33,228,332,395],"transferring":[34,333],"Hydro":[36],"multispectral":[37,335],"foundation":[38,336],"model,":[39],"Swin":[41],"Transformer":[42],"V2":[43],"Base":[44],"encoder":[45,136,189,224,262,269,299],"pretrained":[46,188],"with":[47,302],"SimMIM":[48],"on":[49],"Sentinel-2":[50],"Level-2A":[51],"water-body":[52],"imagery,":[53],"Marine":[56],"Debris":[57],"Oil":[59],"Spill":[60],"(MADOS)":[61],"marine":[62,339],"pollution":[63],"benchmark":[64],"dataset,":[65,379],"processed":[66],"through":[67],"ACOLITE":[68],"Rayleigh":[69],"reflectance":[70,95],"providing":[72],"11":[73],"of":[74,109,155,181,238,305,328,376],"12":[76],"spectral":[77,128,296],"bands":[78,297],"used":[79],"during":[80],"pretraining.":[81],"The":[82,236,355],"two":[83,403],"datasets":[84],"therefore":[86],"produced":[87],"by":[88,165],"different":[89,94],"atmospheric":[90],"correction":[91],"algorithms":[92],"under":[93,351],"conventions,":[96],"resulting":[99],"per-band":[100,311,399],"statistical":[101],"discrepancy":[102],"is":[103,150,359,390],"quantified":[104],"starting":[107],"point":[108],"analysis.":[111],"Three":[112],"dimensions":[114],"then":[116],"systematically":[117],"varied":[118],"while":[119],"all":[120],"other":[121],"settings":[122],"held":[124],"constant:":[125],"input":[126,292],"normalisation,":[127],"band":[129],"adaptation":[130],"missing":[133],"B09,":[134],"transfer":[137,382],"mode.":[138],"From":[139],"this,":[140],"four":[141],"findings":[142],"emerge.":[143],"Normalisation":[144],"training":[147,215,233,245],"inference":[149,389],"single":[152,348],"largest":[153,172],"source":[154,315],"performance":[156],"degradation,":[157],"reducing":[158],"mean":[160],"Intersection":[161],"over":[162],"Union":[163],"(mIoU)":[164],"0.458,":[166],"more":[167,360],"than":[168,260,323,362],"seven":[169],"times":[170],"radiometric":[173],"perturbation":[174],"tested.":[175],"A":[176,366],"zero-parameter":[177],"Frobenius-matched":[178],"column":[179],"crop":[180],"patch":[183],"embedding":[184],"adapts":[185],"12-band":[187],"11-band":[192],"target,":[193],"at":[194,205,388],"least":[195],"effectively":[197],"any":[199,381],"learnt":[200],"linear":[201],"or":[202],"nonlinear":[203],"adapter,":[204],"lower":[207],"cross-seed":[208],"variance.":[209],"Under":[210],"limited":[211,352],"supervision":[213],"(1433":[214],"patches":[216],"against":[217],"an":[218],"87.9":[219],"million-parameter":[220],"encoder),":[221],"freezing":[222],"outperforms":[225],"both":[226],"fine-tuning":[227],"full":[229],"random":[231],"initialisation":[232],"from":[234,385],"scratch.":[235],"gains":[237],"partial":[239],"unfreezing":[240],"attributable":[242],"augmented":[244],"(very":[246],"simple":[247],"copy\u2013paste":[248],"(VSCP)":[249],"augmentation,":[250],"exponential":[251],"moving":[252],"average":[253],"(EMA),":[254],"test-time":[256],"augmentation":[257],"(TTA))":[258],"rather":[259,322],"adaptation.":[263],"With":[264],"matched":[265],"preprocessing,":[266],"frozen":[268,367],"reaches":[270],"0.600":[271],"mIoU":[272],"matches":[274],"published":[276],"MariNeXt":[277],"baseline":[278],"within":[279],"seed":[280],"variability.":[281],"Mechanistic":[282],"analysis":[283],"via":[284],"band-occlusion":[285],"attribution":[286],"feature-space":[288],"separability":[289],"shows":[290],"that":[291,383],"normalisation":[293,374],"determines":[294],"which":[295],"relies":[300],"upon,":[301],"magnitude":[304,364],"shift":[307],"correlated":[308],"gap":[312],"Operationally,":[319],"alignment,":[321],"architectural":[324],"modification,":[325],"carries":[326],"most":[327],"practical":[330],"effort":[331],"model":[337],"surface":[340],"segmentation.":[341],"These":[342],"results":[343],"established":[345],"encoder\u2013benchmark":[349],"pair":[350],"supervision.":[354],"mechanism":[356],"they":[357],"identify":[358],"portable":[361],"reported.":[365],"encoder\u2019s":[368],"representations":[369],"remain":[370],"bound":[371],"statistics":[375,387],"its":[377],"so":[380],"departs":[384],"these":[386],"predicted":[391],"degrade":[393],"sharply":[394],"proportion":[396],"distance":[400]},"counts_by_year":[],"updated_date":"2026-11-06T12:05:46.655746","created_date":"2026-09-01T00:00:00"}
