{"id":"https://openalex.org/W4387803965","doi":"https://doi.org/10.1109/igarss52108.2023.10282163","title":"Transfer-Learning On Land Use And Land Cover Classification","display_name":"Transfer-Learning On Land Use And Land Cover Classification","publication_year":2023,"publication_date":"2023-07-16","ids":{"openalex":"https://openalex.org/W4387803965","doi":"https://doi.org/10.1109/igarss52108.2023.10282163"},"language":"en","primary_location":{"id":"doi:10.1109/igarss52108.2023.10282163","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/igarss52108.2023.10282163","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium","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/A5016278344","display_name":"Gabriel A. Carneiro","orcid":"https://orcid.org/0000-0001-7097-3260"},"institutions":[{"id":"https://openalex.org/I155381812","display_name":"University of Tr\u00e1s-os-Montes and Alto Douro","ror":"https://ror.org/03qc8vh97","country_code":"PT","type":"education","lineage":["https://openalex.org/I155381812"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Gabriel Carneiro","raw_affiliation_strings":["University of Trás-Os-Montes e Alto Douro,Vila Real,Portugal"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Trás-Os-Montes e Alto Douro,Vila Real,Portugal","institution_ids":["https://openalex.org/I155381812"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079354584","display_name":"Ana Cl\u00e1udia Teixeira","orcid":"https://orcid.org/0000-0002-8455-5024"},"institutions":[{"id":"https://openalex.org/I155381812","display_name":"University of Tr\u00e1s-os-Montes and Alto Douro","ror":"https://ror.org/03qc8vh97","country_code":"PT","type":"education","lineage":["https://openalex.org/I155381812"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Ana Teixeira","raw_affiliation_strings":["University of Trás-Os-Montes e Alto Douro,Vila Real,Portugal"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Trás-Os-Montes e Alto Douro,Vila Real,Portugal","institution_ids":["https://openalex.org/I155381812"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103099779","display_name":"A. Cunha","orcid":"https://orcid.org/0000-0002-3458-7693"},"institutions":[{"id":"https://openalex.org/I155381812","display_name":"University of Tr\u00e1s-os-Montes and Alto Douro","ror":"https://ror.org/03qc8vh97","country_code":"PT","type":"education","lineage":["https://openalex.org/I155381812"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Ant\u00f3nio Cunha","raw_affiliation_strings":["University of Trás-Os-Montes e Alto Douro,Vila Real,Portugal"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Trás-Os-Montes e Alto Douro,Vila Real,Portugal","institution_ids":["https://openalex.org/I155381812"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066556659","display_name":"Joaquim J. Sousa","orcid":"https://orcid.org/0000-0003-4533-930X"},"institutions":[{"id":"https://openalex.org/I155381812","display_name":"University of Tr\u00e1s-os-Montes and Alto Douro","ror":"https://ror.org/03qc8vh97","country_code":"PT","type":"education","lineage":["https://openalex.org/I155381812"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Joaquim Sousa","raw_affiliation_strings":["University of Trás-Os-Montes e Alto Douro,Vila Real,Portugal"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Trás-Os-Montes e Alto Douro,Vila Real,Portugal","institution_ids":["https://openalex.org/I155381812"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I155381812"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2918","last_page":"2921"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9991000294685364,"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":0.9991000294685364,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"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/transfer-of-learning","display_name":"Transfer of learning","score":0.7573626041412354},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.723900556564331},{"id":"https://openalex.org/keywords/land-cover","display_name":"Land cover","score":0.7218837738037109},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6427640914916992},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.595580518245697},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5208638310432434},{"id":"https://openalex.org/keywords/cover","display_name":"Cover (algebra)","score":0.5025568008422852},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.49706485867500305},{"id":"https://openalex.org/keywords/window","display_name":"Window (computing)","score":0.4267211854457855},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4161715805530548},{"id":"https://openalex.org/keywords/land-use","display_name":"Land use","score":0.3643829822540283},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.11933192610740662}],"concepts":[{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.7573626041412354},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.723900556564331},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.7218837738037109},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6427640914916992},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.595580518245697},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5208638310432434},{"id":"https://openalex.org/C2780428219","wikidata":"https://www.wikidata.org/wiki/Q16952335","display_name":"Cover (algebra)","level":2,"score":0.5025568008422852},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.49706485867500305},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.4267211854457855},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4161715805530548},{"id":"https://openalex.org/C4792198","wikidata":"https://www.wikidata.org/wiki/Q1165944","display_name":"Land use","level":2,"score":0.3643829822540283},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.11933192610740662},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss52108.2023.10282163","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/igarss52108.2023.10282163","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15","score":0.7099999785423279}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2808098982","https://openalex.org/W2935956419","https://openalex.org/W2964194231","https://openalex.org/W3001279689","https://openalex.org/W3033969337","https://openalex.org/W3099985666","https://openalex.org/W3105357426","https://openalex.org/W3138725786","https://openalex.org/W6772383348"],"related_works":["https://openalex.org/W3133615129","https://openalex.org/W2087854757","https://openalex.org/W2188959887","https://openalex.org/W3176438653","https://openalex.org/W2373152553","https://openalex.org/W2981628807","https://openalex.org/W4389201442","https://openalex.org/W2386169820","https://openalex.org/W604251607","https://openalex.org/W3170595163"],"abstract_inverted_index":{"In":[0],"this":[1],"study,":[2],"we":[3],"evaluated":[4,39],"the":[5,26,35,40,43,64,87,94,97],"use":[6,17],"of":[7,42,56,60,79],"small":[8,27,91],"pre-trained":[9,67],"3D":[10],"Convolutional":[11],"Neural":[12],"Networks":[13],"(CNN)":[14],"on":[15],"land":[16,19],"and":[18,38,58,69],"cover":[20],"(LULC)":[21],"slide-window-based":[22],"classification.":[23],"We":[24],"pretrained":[25],"models":[28,68,74],"in":[29,34],"a":[30],"dataset":[31,37],"with":[32],"origin":[33],"Eurosat":[36],"benefits":[41],"transfer-learning":[44],"plus":[45],"fine-tuning":[46],"for":[47,90],"four":[48],"different":[49],"regions":[50],"using":[51],"Sentinel-2":[52],"L1C":[53],"imagery":[54],"(bands":[55],"10":[57],"20m":[59],"spatial":[61],"resolution),":[62],"comparing":[63],"results":[65],"to":[66,101],"trained":[70],"from":[71],"scratch.":[72],"The":[73],"achieved":[75],"an":[76],"F1":[77],"Score":[78],"between":[80],"0.69-0.80":[81],"without":[82],"significative":[83],"change":[84],"when":[85],"pre-training":[86,93],"model.":[88],"However,":[89],"datasets,":[92],"model":[95],"improved":[96],"classification":[98],"by":[99],"up":[100],"3%.":[102]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}