{"id":"https://openalex.org/W7167584529","doi":"https://doi.org/10.48550/arxiv.2607.03760","title":"GeoSAM-Lite: A Lightweight Foundation Model for Onboard Remote Sensing Segmentation","display_name":"GeoSAM-Lite: A Lightweight Foundation Model for Onboard Remote Sensing Segmentation","publication_year":2026,"publication_date":"2026-07-04","ids":{"openalex":"https://openalex.org/W7167584529","doi":"https://doi.org/10.48550/arxiv.2607.03760"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2607.03760","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2607.03760","pdf_url":"https://arxiv.org/pdf/2607.03760","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","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2607.03760","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136019100","display_name":"Yongcong Wang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I167027274","display_name":"Nanjing Forestry University","ror":"https://ror.org/03m96p165","country_code":"CN","type":"education","lineage":["https://openalex.org/I167027274"]},{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wang, Yongcong","raw_affiliation_strings":["College of Information Science and Technology & Artificial Intelligence , Nanjing Forestry University , Nanjing 210016 , China","College of Telecommunications and Information Engineer- ing , Nanjing University of Posts and Telecommunications , Nanjing 210003 , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology & Artificial Intelligence , Nanjing Forestry University , Nanjing 210016 , China","institution_ids":["https://openalex.org/I167027274"]},{"raw_affiliation_string":"College of Telecommunications and Information Engineer- ing , Nanjing University of Posts and Telecommunications , Nanjing 210003 , China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140163346","display_name":"Jie M. Zhang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I167027274","display_name":"Nanjing Forestry University","ror":"https://ror.org/03m96p165","country_code":"CN","type":"education","lineage":["https://openalex.org/I167027274"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhang, Jie","raw_affiliation_strings":["College of Information Science and Technology & Artificial Intelligence , Nanjing Forestry University , Nanjing 210016 , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology & Artificial Intelligence , Nanjing Forestry University , Nanjing 210016 , China","institution_ids":["https://openalex.org/I167027274"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140185637","display_name":"Rui Jiang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I167027274","display_name":"Nanjing Forestry University","ror":"https://ror.org/03m96p165","country_code":"CN","type":"education","lineage":["https://openalex.org/I167027274"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiang, Rui","raw_affiliation_strings":["College of Information Science and Technology & Artificial Intelligence , Nanjing Forestry University , Nanjing 210016 , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology & Artificial Intelligence , Nanjing Forestry University , Nanjing 210016 , China","institution_ids":["https://openalex.org/I167027274"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028328877","display_name":"Xubing Yang","orcid":"https://orcid.org/0000-0001-5504-8392","observed_orcids":["https://orcid.org/0000-0001-5504-8392"]},"institutions":[{"id":"https://openalex.org/I167027274","display_name":"Nanjing Forestry University","ror":"https://ror.org/03m96p165","country_code":"CN","type":"education","lineage":["https://openalex.org/I167027274"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang, Xubing","raw_affiliation_strings":["College of Information Science and Technology & Artificial Intelligence , Nanjing Forestry University , Nanjing 210016 , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology & Artificial Intelligence , Nanjing Forestry University , Nanjing 210016 , China","institution_ids":["https://openalex.org/I167027274"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133110004","display_name":"Ting Yun","orcid":"https://orcid.org/0000-0003-4294-8337","observed_orcids":["https://orcid.org/0000-0003-4294-8337"]},"institutions":[{"id":"https://openalex.org/I167027274","display_name":"Nanjing Forestry University","ror":"https://ror.org/03m96p165","country_code":"CN","type":"education","lineage":["https://openalex.org/I167027274"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yun, Ting","raw_affiliation_strings":["College of Information Science and Technology & Artificial Intelligence , Nanjing Forestry University , Nanjing 210016 , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology & Artificial Intelligence , Nanjing Forestry University , Nanjing 210016 , China","institution_ids":["https://openalex.org/I167027274"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5140162980","display_name":"Li Lyna Zhang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I167027274","display_name":"Nanjing Forestry University","ror":"https://ror.org/03m96p165","country_code":"CN","type":"education","lineage":["https://openalex.org/I167027274"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhang, Li","raw_affiliation_strings":["College of Information Science and Technology & Artificial Intelligence , Nanjing Forestry University , Nanjing 210016 , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology & Artificial Intelligence , Nanjing Forestry University , Nanjing 210016 , China","institution_ids":["https://openalex.org/I167027274"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.7188000082969666,"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":0.7188000082969666,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.2678000032901764,"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":0.006800000090152025,"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/segment-anything-model","display_name":"Segment Anything Model","score":0.8949999809265137},{"id":"https://openalex.org/keywords/remote-sensing-image-segmentation","display_name":"remote sensing image segmentation","score":0.859000027179718},{"id":"https://openalex.org/keywords/onboard-processing","display_name":"on-board processing","score":0.550000011920929},{"id":"https://openalex.org/keywords/edge-devices","display_name":"edge devices","score":0.6579999923706055},{"id":"https://openalex.org/keywords/domain-shift","display_name":"domain shift","score":0.6499999761581421},{"id":"https://openalex.org/keywords/knowledge-distillation","display_name":"knowledge distillation","score":0.8899999856948853},{"id":"https://openalex.org/keywords/feature-fusion","display_name":"feature fusion","score":0.878000020980835},{"id":"https://openalex.org/keywords/real-time-segmentation","display_name":"real-time segmentation","score":0.6930000185966492}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7078999876976013},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.609000027179718},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5946000218391418},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5629000067710876},{"id":"https://openalex.org/C161840515","wikidata":"https://www.wikidata.org/wiki/Q186131","display_name":"Terrain","level":2,"score":0.5623999834060669},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.5304999947547913},{"id":"https://openalex.org/C9770341","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Geospatial analysis","level":2,"score":0.5085999965667725},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4828000068664551},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4672999978065491},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.43389999866485596},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.42340001463890076},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.40049999952316284},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.39879998564720154},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3917999863624573},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3806999921798706},{"id":"https://openalex.org/C183365957","wikidata":"https://www.wikidata.org/wiki/Q17140402","display_name":"Remote sensing application","level":3,"score":0.3797999918460846},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.36250001192092896},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.3571999967098236},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.35280001163482666},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3467000126838684},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.3370000123977661},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.3206999897956848},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.31200000643730164},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.311599999666214},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.30630001425743103},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.30160000920295715},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.28459998965263367},{"id":"https://openalex.org/C137635306","wikidata":"https://www.wikidata.org/wiki/Q182667","display_name":"Pareto principle","level":2,"score":0.2822999954223633},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.27720001339912415},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.2669999897480011},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.26409998536109924},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2547999918460846},{"id":"https://openalex.org/C39399123","wikidata":"https://www.wikidata.org/wiki/Q1348989","display_name":"Earth observation","level":3,"score":0.2538999915122986},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.25270000100135803}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2607.03760","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2607.03760","pdf_url":"https://arxiv.org/pdf/2607.03760","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","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2607.03760","doi":"https://doi.org/10.48550/arxiv.2607.03760","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.03760","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","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2607.03760","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2607.03760","pdf_url":"https://arxiv.org/pdf/2607.03760","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","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5378999710083008}],"study_designs":[],"awards":[{"id":"https://openalex.org/G212259472","display_name":null,"funder_award_id":"32371876","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7167584529.pdf","grobid_xml":"https://content.openalex.org/works/W7167584529.grobid-xml"},"referenced_works_count":5,"referenced_works":["https://openalex.org/W4225871896","https://openalex.org/W4382322597","https://openalex.org/W4390874575","https://openalex.org/W4391021462","https://openalex.org/W4402727760"],"related_works":["https://openalex.org/W4416728837","https://openalex.org/W7131106872","https://openalex.org/W4417339136","https://openalex.org/W7164206976","https://openalex.org/W7212430611","https://openalex.org/W7117703024","https://openalex.org/W7214012688","https://openalex.org/W7170187620","https://openalex.org/W7161154175","https://openalex.org/W7161939361"],"abstract_inverted_index":{"The":[0],"deployment":[1],"of":[2,101],"large-scale":[3],"foundation":[4],"models":[5],"like":[6],"Segment":[7],"Anything":[8],"Model":[9],"(SAM)":[10],"on":[11,112,159],"resource-constrained":[12],"Earth":[13],"observation":[14],"platforms":[15],"is":[16],"hindered":[17],"by":[18,134],"prohibitive":[19],"computational":[20],"costs":[21],"and":[22,28,81,91,122,149],"the":[23,78,98,138],"domain":[24,79],"shift":[25],"between":[26,147],"natural":[27],"remote":[29,52],"sensing":[30,53],"imagery.":[31],"To":[32],"address":[33],"these":[34],"challenges,":[35],"we":[36],"propose":[37],"\\textit{Geo}spatial":[38],"\\textit{S}egment":[39],"\\textit{A}nything":[40],"\\textit{M}odel-Lite":[41],"(GeoSAM-Lite),":[42],"a":[43,64,73,109,143,153],"lightweight,":[44],"prompt-free":[45],"segmentation":[46,158],"framework":[47],"designed":[48],"for":[49,156],"efficient":[50],"onboard":[51],"segmentation.":[54],"GeoSAM-Lite":[55,127,151],"incorporates":[56],"two":[57],"core":[58],"innovations:":[59],"(1)":[60],"Geospatial-Domain":[61],"Initialization":[62],"(Geo-Init),":[63],"domain-aware":[65],"pre-training":[66],"strategy":[67],"that":[68,126],"distills":[69],"geospatial":[70],"priors":[71],"from":[72],"specialized":[74],"teacher":[75],"to":[76,96,115,137],"bridge":[77],"gap;":[80],"(2)":[82],"Feature":[83],"Fusion":[84],"Layers":[85],"(FFL),":[86],"which":[87],"recalibrate":[88],"spatial":[89],"features":[90],"restore":[92],"high-frequency":[93],"boundary":[94],"cues":[95],"overcome":[97],"capacity":[99],"bottlenecks":[100],"lightweight":[102],"backbones.":[103],"Experiments":[104],"across":[105],"representative":[106],"datasets,":[107],"with":[108],"primary":[110],"focus":[111],"cloud":[113],"scenarios":[114],"evaluate":[116],"performance":[117],"under":[118],"extreme":[119],"scale":[120],"variations":[121],"complex":[123],"boundaries,":[124],"demonstrate":[125],"achieves":[128],"competitive":[129],"accuracy":[130],"while":[131],"reducing":[132],"parameters":[133],"92.8\\%":[135],"compared":[136],"heavyweight":[139],"RSAM-Seg.":[140],"By":[141],"establishing":[142],"superior":[144],"Pareto":[145],"frontier":[146],"efficiency":[148],"fidelity,":[150],"offers":[152],"practical":[154],"solution":[155],"real-time":[157],"edge":[160],"devices.":[161]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-07-08T00:00:00"}
