{"id":"https://openalex.org/W4205087189","doi":"https://doi.org/10.1109/jstars.2022.3141063","title":"Accounting for Label Errors When Training a Convolutional Neural Network to Estimate Sea Ice Concentration Using Operational Ice Charts","display_name":"Accounting for Label Errors When Training a Convolutional Neural Network to Estimate Sea Ice Concentration Using Operational Ice Charts","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4205087189","doi":"https://doi.org/10.1109/jstars.2022.3141063"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2022.3141063","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2022.3141063","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/9656571/09674865.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/4609443/9656571/09674865.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062781779","display_name":"Manveer Singh Tamber","orcid":null},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Manveer Singh Tamber","raw_affiliation_strings":["David R. Cheriton School of Computer Science, University of Waterloo, Waterloo, ON, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"David R. Cheriton School of Computer Science, University of Waterloo, Waterloo, ON, Canada","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083200788","display_name":"K. Andrea Scott","orcid":"https://orcid.org/0000-0003-3922-8777"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"K. Andrea Scott","raw_affiliation_strings":["Department of Systems Design Engineering, University of Waterloo, Waterloo, ON, Canada"],"raw_orcid":"https://orcid.org/0000-0003-3922-8777","affiliations":[{"raw_affiliation_string":"Department of Systems Design Engineering, University of Waterloo, Waterloo, ON, Canada","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056017119","display_name":"Leif Toudal Pedersen","orcid":"https://orcid.org/0000-0001-7913-6282"},"institutions":[{"id":"https://openalex.org/I96673099","display_name":"Technical University of Denmark","ror":"https://ror.org/04qtj9h94","country_code":"DK","type":"education","lineage":["https://openalex.org/I96673099"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Leif Toudal Pedersen","raw_affiliation_strings":["DTU Space, Technical University of Denmark, Kongens Lyngby, Denmark"],"raw_orcid":"https://orcid.org/0000-0001-7913-6282","affiliations":[{"raw_affiliation_string":"DTU Space, Technical University of Denmark, Kongens Lyngby, Denmark","institution_ids":["https://openalex.org/I96673099"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":{"value":1250,"currency":"USD","value_usd":1250},"fwci":2.4794,"has_fulltext":true,"cited_by_count":22,"citation_normalized_percentile":{"value":0.88280185,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"15","issue":null,"first_page":"1502","last_page":"1513"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11459","display_name":"Arctic and Antarctic ice dynamics","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11459","display_name":"Arctic and Antarctic ice dynamics","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"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/T12696","display_name":"Icing and De-icing Technologies","score":0.9763000011444092,"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"}},{"id":"https://openalex.org/T12316","display_name":"Oil Spill Detection and Mitigation","score":0.9470999836921692,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.593750536441803},{"id":"https://openalex.org/keywords/sea-ice","display_name":"Sea ice","score":0.5745847821235657},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5497718453407288},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.5365349054336548},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42012858390808105},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24863091111183167},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.21262913942337036},{"id":"https://openalex.org/keywords/climatology","display_name":"Climatology","score":0.19657814502716064},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.1825367510318756},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.06835341453552246}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.593750536441803},{"id":"https://openalex.org/C136894858","wikidata":"https://www.wikidata.org/wiki/Q213926","display_name":"Sea ice","level":2,"score":0.5745847821235657},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5497718453407288},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.5365349054336548},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42012858390808105},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24863091111183167},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.21262913942337036},{"id":"https://openalex.org/C49204034","wikidata":"https://www.wikidata.org/wiki/Q52139","display_name":"Climatology","level":1,"score":0.19657814502716064},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.1825367510318756},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.06835341453552246}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/jstars.2022.3141063","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2022.3141063","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/9656571/09674865.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:165a8e97b6614909bf43bbbfd7df6780","is_oa":true,"landing_page_url":"https://doaj.org/article/165a8e97b6614909bf43bbbfd7df6780","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,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 15, Pp 1502-1513 (2022)","raw_type":"article"},{"id":"pmh:oai:pure.atira.dk:publications/34900a9f-d9c2-4cab-aa10-13845b8552c8","is_oa":true,"landing_page_url":"https://orbit.dtu.dk/en/publications/34900a9f-d9c2-4cab-aa10-13845b8552c8","pdf_url":null,"source":{"id":"https://openalex.org/S4306400705","display_name":"Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I96673099","host_organization_name":"Technical University of Denmark","host_organization_lineage":["https://openalex.org/I96673099"],"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":"Tamber , M , Scott , K A & Pedersen , L T 2022 , ' Accounting for label errors when training a convolutional neural network to estimate sea ice concentration using operational ice charts ' , IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , vol. 15 , pp. 1502-1513 . https://doi.org/10.1109/JSTARS.2022.3141063","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/jstars.2022.3141063","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2022.3141063","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/9656571/09674865.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Life below water","score":0.8700000047683716,"id":"https://metadata.un.org/sdg/14"}],"awards":[{"id":"https://openalex.org/G7688043556","display_name":null,"funder_award_id":"GCXE20M002","funder_id":"https://openalex.org/F4320325263","funder_display_name":"Environment and Climate Change Canada"}],"funders":[{"id":"https://openalex.org/F4320314000","display_name":"Compute Canada","ror":"https://ror.org/03ty8yr27"},{"id":"https://openalex.org/F4320319864","display_name":"ArcticNet","ror":"https://ror.org/01tca3t44"},{"id":"https://openalex.org/F4320322676","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68"},{"id":"https://openalex.org/F4320325263","display_name":"Environment and Climate Change Canada","ror":"https://ror.org/026ny0e17"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4205087189.pdf","grobid_xml":"https://content.openalex.org/works/W4205087189.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W1922460326","https://openalex.org/W1979124440","https://openalex.org/W2004817876","https://openalex.org/W2017975941","https://openalex.org/W2068258889","https://openalex.org/W2072996485","https://openalex.org/W2074145556","https://openalex.org/W2096413136","https://openalex.org/W2149635781","https://openalex.org/W2412782625","https://openalex.org/W2525801532","https://openalex.org/W2608569001","https://openalex.org/W2772239202","https://openalex.org/W2912226897","https://openalex.org/W2912523934","https://openalex.org/W2915023258","https://openalex.org/W3036494218","https://openalex.org/W3038391328","https://openalex.org/W3040593397","https://openalex.org/W3047096992","https://openalex.org/W3158152196","https://openalex.org/W4213251304","https://openalex.org/W6727621913","https://openalex.org/W6728622933"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W230091440","https://openalex.org/W2390279801","https://openalex.org/W2233261550","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2810751659"],"abstract_inverted_index":{"Convolutional":[0],"neural":[1],"networks":[2],"(CNNs)":[3],"are":[4,174],"being":[5],"increasingly":[6],"investigated":[7],"as":[8,32],"a":[9,46,53,112],"means":[10],"to":[11,45,69,89,95,99,114,132,134,139,151],"extract":[12],"sea":[13,56,79,154,180],"ice":[14,30,40,57,80,92,107,117,142,155,181],"concentration":[15,41,58,156,182],"from":[16,149,183],"synthetic":[17],"aperture":[18],"radar":[19],"(SAR)":[20],"in":[21,36,124,137,176],"an":[22,39],"automated":[23],"manner.":[24],"This":[25,67],"is":[26,43,130],"often":[27],"done":[28],"using":[29,140],"charts":[31],"training":[33],"data.":[34,186],"However,":[35],"these":[37],"charts,":[38],"label":[42,103],"given":[44],"large":[47],"region,":[48],"which":[49,72],"may":[50],"not":[51],"have":[52,163],"spatially":[54],"uniform":[55],"distribution":[59],"at":[60,77],"the":[61,65,91,102,116,122,125,141,159,168,184],"prediction":[62],"scale":[63],"of":[64],"CNN.":[66],"leads":[68],"representativity":[70],"errors,":[71],"can":[73],"be":[74],"more":[75],"pronounced":[76],"intermediate":[78,106],"concentrations.":[81,108],"In":[82],"this":[83],"study,":[84],"we":[85],"first":[86],"investigate":[87],"ways":[88],"perturb":[90],"chart":[93,118,143],"labels":[94,144,161],"obtain":[96],"improved":[97,135],"predictions":[98],"account":[100],"for":[101,105],"uncertainty":[104],"We":[109],"then":[110],"propose":[111],"method":[113,129],"augment":[115],"data":[119],"by":[120],"rescaling":[121],"information":[123],"SAR":[126,185],"imagery.":[127],"The":[128,153],"found":[131],"lead":[133],"accuracy":[136,147],"comparison":[138],"alone,":[145],"with":[146,158,178],"improving":[148],"0.919":[150],"0.966.":[152],"maps":[157],"augmented":[160],"also":[162],"much":[164],"finer":[165],"detail":[166],"than":[167],"other":[169],"approaches":[170],"evaluated.":[171],"These":[172],"details":[173],"visually":[175],"agreement":[177],"expected":[179]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}