{"id":"https://openalex.org/W2794954404","doi":"https://doi.org/10.1109/tgrs.2018.2833808","title":"Low-Shot Learning for the Semantic Segmentation of Remote Sensing Imagery","display_name":"Low-Shot Learning for the Semantic Segmentation of Remote Sensing Imagery","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2794954404","doi":"https://doi.org/10.1109/tgrs.2018.2833808","mag":"2794954404"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2018.2833808","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2018.2833808","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"},"type":"article","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/A5043035821","display_name":"Ronald Kemker","orcid":"https://orcid.org/0000-0003-4087-4952"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ronald Kemker","raw_affiliation_strings":["Machine and Neuromorphic Perception Laboratory, Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY, USA"],"raw_orcid":"https://orcid.org/0000-0003-4087-4952","affiliations":[{"raw_affiliation_string":"Machine and Neuromorphic Perception Laboratory, Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY, USA","institution_ids":["https://openalex.org/I155173764"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015003956","display_name":"Ryan Luu","orcid":null},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ryan Luu","raw_affiliation_strings":["Machine and Neuromorphic Perception Laboratory, Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Machine and Neuromorphic Perception Laboratory, Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY, USA","institution_ids":["https://openalex.org/I155173764"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046979072","display_name":"Christopher Kanan","orcid":"https://orcid.org/0000-0002-6412-995X"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christopher Kanan","raw_affiliation_strings":["Machine and Neuromorphic Perception Laboratory, Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Machine and Neuromorphic Perception Laboratory, Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY, USA","institution_ids":["https://openalex.org/I155173764"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I155173764"],"apc_list":null,"apc_paid":null,"fwci":6.0778,"has_fulltext":false,"cited_by_count":63,"citation_normalized_percentile":{"value":0.96354258,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998000264167786,"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":0.9998000264167786,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9941999912261963,"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":0.9901000261306763,"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/computer-science","display_name":"Computer science","score":0.8361681699752808},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7157551050186157},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5728809833526611},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5575736165046692},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.5299668908119202},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5115240812301636},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4791818857192993},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.47737810015678406},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45608824491500854},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.429146409034729},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42536163330078125},{"id":"https://openalex.org/keywords/automatic-image-annotation","display_name":"Automatic image annotation","score":0.42286908626556396},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.4138796329498291},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.39337706565856934},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.3624405860900879},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2986607551574707}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8361681699752808},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7157551050186157},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5728809833526611},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5575736165046692},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.5299668908119202},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5115240812301636},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4791818857192993},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.47737810015678406},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45608824491500854},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.429146409034729},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42536163330078125},{"id":"https://openalex.org/C199579030","wikidata":"https://www.wikidata.org/wiki/Q2851778","display_name":"Automatic image annotation","level":4,"score":0.42286908626556396},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.4138796329498291},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39337706565856934},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.3624405860900879},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2986607551574707},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tgrs.2018.2833808","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2018.2833808","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:scholarworks.rit.edu:theses-10995","is_oa":false,"landing_page_url":"https://scholarworks.rit.edu/theses/9834","pdf_url":null,"source":{"id":"https://openalex.org/S4306402456","display_name":"RIT Scholar Works (Rochester Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I155173764","host_organization_name":"Rochester Institute of Technology","host_organization_lineage":["https://openalex.org/I155173764"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Theses","raw_type":"text"},{"id":"pmh:oai:repository.rit.edu:theses-10995","is_oa":false,"landing_page_url":"https://repository.rit.edu/theses/9834","pdf_url":null,"source":{"id":"https://openalex.org/S4306402456","display_name":"RIT Scholar Works (Rochester Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I155173764","host_organization_name":"Rochester Institute of Technology","host_organization_lineage":["https://openalex.org/I155173764"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Theses","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6700000166893005,"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320309036","display_name":"Purdue University","ror":"https://ror.org/02dqehb95"},{"id":"https://openalex.org/F4320309398","display_name":"California Institute of Technology","ror":"https://ror.org/05dxps055"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1485235332","https://openalex.org/W1491705651","https://openalex.org/W1533861849","https://openalex.org/W1843514792","https://openalex.org/W1843779453","https://openalex.org/W1983326850","https://openalex.org/W1990895816","https://openalex.org/W2005672614","https://openalex.org/W2008509935","https://openalex.org/W2057540576","https://openalex.org/W2105386417","https://openalex.org/W2117885496","https://openalex.org/W2120353970","https://openalex.org/W2122922389","https://openalex.org/W2142012908","https://openalex.org/W2147062276","https://openalex.org/W2153409933","https://openalex.org/W2155658307","https://openalex.org/W2160654481","https://openalex.org/W2169042894","https://openalex.org/W2329928123","https://openalex.org/W2341171179","https://openalex.org/W2592224809","https://openalex.org/W2601762297","https://openalex.org/W2620547787","https://openalex.org/W2903382683","https://openalex.org/W2952229419","https://openalex.org/W2963285578","https://openalex.org/W2963373786","https://openalex.org/W2963568027","https://openalex.org/W3105255022","https://openalex.org/W6623329352","https://openalex.org/W6631943919","https://openalex.org/W6685562342","https://openalex.org/W6715932150","https://openalex.org/W6718379498","https://openalex.org/W6757107679","https://openalex.org/W6786371059"],"related_works":["https://openalex.org/W3177930984","https://openalex.org/W2792279927","https://openalex.org/W2052697133","https://openalex.org/W4385497869","https://openalex.org/W2076896210","https://openalex.org/W283587633","https://openalex.org/W2093596879","https://openalex.org/W2384288472","https://openalex.org/W1539573266","https://openalex.org/W2376984068"],"abstract_inverted_index":{"Recent":[0],"advances":[1],"in":[2,47],"computer":[3],"vision":[4],"using":[5,101],"deep":[6],"learning":[7,82,100,104,115,151],"with":[8],"RGB":[9,27],"imagery":[10,71],"(e.g.,":[11],"object":[12],"recognition":[13],"and":[14,36,119,122,160],"detection)":[15],"have":[16,143],"been":[17],"made":[18],"possible":[19],"thanks":[20],"to":[21,50,77],"the":[22,51,134,155],"development":[23],"of":[24,54,68,91],"large":[25],"annotated":[26,92,145],"image":[28,34,38,79,157],"data":[29,40,121,140,147],"sets.":[30],"In":[31,94],"contrast,":[32],"multispectral":[33],"(MSI)":[35],"hyperspectral":[37],"(HSI)":[39],"sets":[41,141],"contain":[42],"far":[43],"fewer":[44],"labeled":[45],"images,":[46],"part":[48],"due":[49],"wide":[52],"variety":[53],"sensors":[55],"used.":[56],"These":[57,149],"annotations":[58],"are":[59,130],"especially":[60],"limited":[61],"for":[62,105,117,165],"semantic":[63,106,162],"segmentation,":[64],"or":[65],"pixelwise":[66],"classification,":[67],"remote":[69,138,166],"sensing":[70,139,167],"because":[72],"it":[73],"is":[74],"labor":[75],"intensive":[76],"generate":[78],"annotations.":[80],"Low-shot":[81],"algorithms":[83],"can":[84],"make":[85],"effective":[86],"inferences":[87],"despite":[88],"smaller":[89],"amounts":[90],"data.":[93],"this":[95],"paper,":[96],"we":[97],"study":[98],"low-shot":[99,150],"self-taught":[102,113],"feature":[103,114],"segmentation.":[107],"We":[108],"introduce:":[109],"1)":[110],"an":[111],"improved":[112],"framework":[116],"HSI":[118],"MSI":[120],"2)":[123],"a":[124],"semisupervised":[125],"classification":[126],"algorithm.":[127],"When":[128],"these":[129],"combined,":[131],"they":[132],"achieve":[133],"state-of-the-art":[135],"performance":[136,164],"on":[137],"that":[142],"little":[144],"training":[146],"available.":[148],"frameworks":[152],"will":[153],"reduce":[154],"manual":[156],"annotation":[158],"burden":[159],"improve":[161],"segmentation":[163],"imagery.":[168]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":15},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":4}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}
