{"id":"https://openalex.org/W3206487315","doi":"https://doi.org/10.1109/igarss47720.2021.9553266","title":"Towards Out-of-Distribution Detection for Remote Sensing","display_name":"Towards Out-of-Distribution Detection for Remote Sensing","publication_year":2021,"publication_date":"2021-07-11","ids":{"openalex":"https://openalex.org/W3206487315","doi":"https://doi.org/10.1109/igarss47720.2021.9553266","mag":"3206487315"},"language":"en","primary_location":{"id":"doi:10.1109/igarss47720.2021.9553266","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss47720.2021.9553266","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089829631","display_name":"Jakob Gawlikowski","orcid":null},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jakob Gawlikowski","raw_affiliation_strings":["Data Science in Earth Observation, Technical University of Munich, Taufkirchen/Ottobrunn, Germany","Institute of Data Science, DLR, Jena, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data Science in Earth Observation, Technical University of Munich, Taufkirchen/Ottobrunn, Germany","institution_ids":["https://openalex.org/I62916508"]},{"raw_affiliation_string":"Institute of Data Science, DLR, Jena, Germany","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083424027","display_name":"Sudipan Saha","orcid":"https://orcid.org/0000-0002-9440-0720"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Sudipan Saha","raw_affiliation_strings":["Data Science in Earth Observation, Technical University of Munich, Taufkirchen/Ottobrunn, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data Science in Earth Observation, Technical University of Munich, Taufkirchen/Ottobrunn, Germany","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050670407","display_name":"Anna Kruspe","orcid":"https://orcid.org/0000-0002-2041-9453"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Anna Kruspe","raw_affiliation_strings":["Data Science in Earth Observation, Technical University of Munich, Taufkirchen/Ottobrunn, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data Science in Earth Observation, Technical University of Munich, Taufkirchen/Ottobrunn, Germany","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068384981","display_name":"Xiao Xiang Zhu","orcid":"https://orcid.org/0000-0001-5530-3613"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Xiao Xiang Zhu","raw_affiliation_strings":["Data Science in Earth Observation, Technical University of Munich, Taufkirchen/Ottobrunn, Germany","Remote Sensing Technology Institute, DLR, We\u00dfling, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data Science in Earth Observation, Technical University of Munich, Taufkirchen/Ottobrunn, Germany","institution_ids":["https://openalex.org/I62916508"]},{"raw_affiliation_string":"Remote Sensing Technology Institute, DLR, We\u00dfling, Germany","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I62916508"],"apc_list":null,"apc_paid":null,"fwci":2.5376,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.91859438,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"8676","last_page":"8679"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9945999979972839,"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"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9945999979972839,"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/T11588","display_name":"Atmospheric and Environmental Gas Dynamics","score":0.9929999709129333,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"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/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9627000093460083,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7248681783676147},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.6502065658569336},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5711000561714172},{"id":"https://openalex.org/keywords/test-data","display_name":"Test data","score":0.5501428842544556},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5099116563796997},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5058343410491943},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.46705687046051025},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.46608278155326843},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4560546576976776},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.45068636536598206},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.44378215074539185},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.43988409638404846},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4103184938430786},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.12670260667800903},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.07636186480522156}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7248681783676147},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.6502065658569336},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5711000561714172},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.5501428842544556},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5099116563796997},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5058343410491943},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.46705687046051025},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.46608278155326843},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4560546576976776},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.45068636536598206},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.44378215074539185},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.43988409638404846},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4103184938430786},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.12670260667800903},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.07636186480522156},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/igarss47720.2021.9553266","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss47720.2021.9553266","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","raw_type":"proceedings-article"},{"id":"pmh:oai:elib.dlr.de:145041","is_oa":false,"landing_page_url":"https://doi.org/10.1109/IGARSS47720.2021.9553266>.","pdf_url":null,"source":{"id":"https://openalex.org/S4377196266","display_name":"elib (German Aerospace Center)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2898391981","host_organization_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","host_organization_lineage":["https://openalex.org/I2898391981"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"Konferenzbeitrag"},{"id":"pmh:oai:elib.dlr.de:142166","is_oa":false,"landing_page_url":"https://elib.dlr.de/142166/","pdf_url":null,"source":{"id":"https://openalex.org/S4377196266","display_name":"elib (German Aerospace Center)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2898391981","host_organization_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","host_organization_lineage":["https://openalex.org/I2898391981"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Konferenzbeitrag"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1594039573","https://openalex.org/W2112884102","https://openalex.org/W2788907134","https://openalex.org/W2806471870","https://openalex.org/W2890651561","https://openalex.org/W2963215553","https://openalex.org/W2963238274","https://openalex.org/W3031928995","https://openalex.org/W3036616251","https://openalex.org/W3094466514","https://openalex.org/W3131769019","https://openalex.org/W4237192424","https://openalex.org/W6730042731","https://openalex.org/W6748865747","https://openalex.org/W6784485370","https://openalex.org/W6790812605"],"related_works":["https://openalex.org/W4223943233","https://openalex.org/W4312200629","https://openalex.org/W4360585206","https://openalex.org/W4364306694","https://openalex.org/W4380086463","https://openalex.org/W4221136938","https://openalex.org/W4213225422","https://openalex.org/W2908875379","https://openalex.org/W4206762304","https://openalex.org/W3200006281"],"abstract_inverted_index":{"In":[0,73,95],"remote":[1,92,104,148],"sensing,":[2],"distributional":[3,49,86],"mismatch":[4],"between":[5,115],"the":[6,21,26,52,66,112,116,140],"training":[7,53],"and":[8,29,118],"test":[9,22,44,129,136],"data":[10,45,63],"may":[11,36],"arise":[12],"due":[13],"to":[14,43,61,84,110],"several":[15],"reasons,":[16],"including":[17],"unseen":[18],"classes":[19],"in":[20,25,38,147],"data,":[23,54],"differences":[24],"geographic":[27],"area,":[28],"multi-sensor":[30],"differences.":[31],"Deep":[32],"learning":[33,70,90],"based":[34,71,91],"models":[35],"behave":[37],"unexpected":[39],"manners":[40],"when":[41],"subjected":[42],"that":[46,139],"has":[47],"such":[48],"shifts":[50],"from":[51],"also":[55],"called":[56],"out-of-distribution":[57],"(OOD)":[58],"examples.":[59],"Vulnerability":[60],"OOD":[62,119,145],"severely":[64],"reduces":[65],"reliability":[67],"of":[68,88,125],"deep":[69,89],"models.":[72,94],"this":[74,78],"work,":[75],"we":[76,97],"address":[77],"issue":[79],"by":[80],"proposing":[81],"a":[82,99,122],"model":[83,142],"quantify":[85],"uncertainty":[87],"sensing":[93,105],"particular,":[96],"adopt":[98],"Dirichlet":[100],"Prior":[101],"Network":[102],"for":[103,121],"data.":[106],"The":[107],"approach":[108],"seeks":[109],"maximize":[111],"representation":[113],"gap":[114],"in-domain":[117],"examples":[120,127],"better":[123],"identification":[124],"unknown":[126],"at":[128],"time.":[130],"Experimental":[131],"results":[132],"on":[133],"three":[134],"exemplary":[135],"scenarios":[137],"show":[138],"proposed":[141],"can":[143],"detect":[144],"images":[146],"sensing.":[149]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}