{"id":"https://openalex.org/W2900573306","doi":"https://doi.org/10.3390/rs11050523","title":"Temporal Convolutional Neural Network for the Classification of Satellite Image Time Series","display_name":"Temporal Convolutional Neural Network for the Classification of Satellite Image Time Series","publication_year":2019,"publication_date":"2019-03-04","ids":{"openalex":"https://openalex.org/W2900573306","doi":"https://doi.org/10.3390/rs11050523","mag":"2900573306"},"language":"en","primary_location":{"id":"doi:10.3390/rs11050523","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs11050523","pdf_url":"https://www.mdpi.com/2072-4292/11/5/523/pdf?version=1551870276","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/11/5/523/pdf?version=1551870276","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032732048","display_name":"Charlotte Pelletier","orcid":"https://orcid.org/0000-0002-4652-7778"},"institutions":[{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Charlotte Pelletier","raw_affiliation_strings":["Faculty of Information Technology, Monash University, Melbourne, VIC 3800, Australia","Monash#N#        University"],"affiliations":[{"raw_affiliation_string":"Faculty of Information Technology, Monash University, Melbourne, VIC 3800, Australia","institution_ids":["https://openalex.org/I56590836"]},{"raw_affiliation_string":"Monash#N#        University","institution_ids":["https://openalex.org/I56590836"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058054791","display_name":"Geoffrey I. Webb","orcid":"https://orcid.org/0000-0001-9963-5169"},"institutions":[{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Geoffrey Webb","raw_affiliation_strings":["Faculty of Information Technology, Monash University, Melbourne, VIC 3800, Australia","Department of Data Science & AI"],"affiliations":[{"raw_affiliation_string":"Faculty of Information Technology, Monash University, Melbourne, VIC 3800, Australia","institution_ids":["https://openalex.org/I56590836"]},{"raw_affiliation_string":"Department of Data Science & AI","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005781957","display_name":"Fran\u00e7ois Petitjean","orcid":"https://orcid.org/0000-0001-5334-3574"},"institutions":[{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Fran\u00e7ois Petitjean","raw_affiliation_strings":["Faculty of Information Technology, Monash University, Melbourne, VIC 3800, Australia","Department of Data Science & AI"],"affiliations":[{"raw_affiliation_string":"Faculty of Information Technology, Monash University, Melbourne, VIC 3800, Australia","institution_ids":["https://openalex.org/I56590836"]},{"raw_affiliation_string":"Department of Data Science & AI","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5032732048"],"corresponding_institution_ids":["https://openalex.org/I56590836"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":5.0253,"has_fulltext":true,"cited_by_count":40,"citation_normalized_percentile":{"value":0.95313996,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"11","issue":"5","first_page":"523","last_page":"523"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9993000030517578,"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"}},"topics":[{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9993000030517578,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9958000183105469,"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/T10226","display_name":"Land Use and Ecosystem Services","score":0.9811999797821045,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6879341006278992},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5880727171897888},{"id":"https://openalex.org/keywords/land-cover","display_name":"Land cover","score":0.5673832893371582},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5345980525016785},{"id":"https://openalex.org/keywords/temporal-database","display_name":"Temporal database","score":0.48506298661231995},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.4777921140193939},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.46064072847366333},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4508405327796936},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4406055808067322},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43494921922683716},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.43493422865867615},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4180380702018738},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.4102478623390198},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32032403349876404},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3046506643295288},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.23104462027549744},{"id":"https://openalex.org/keywords/land-use","display_name":"Land use","score":0.1581314206123352}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6879341006278992},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5880727171897888},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.5673832893371582},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5345980525016785},{"id":"https://openalex.org/C77277458","wikidata":"https://www.wikidata.org/wiki/Q1969246","display_name":"Temporal database","level":2,"score":0.48506298661231995},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.4777921140193939},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.46064072847366333},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4508405327796936},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4406055808067322},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43494921922683716},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.43493422865867615},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4180380702018738},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.4102478623390198},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32032403349876404},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3046506643295288},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.23104462027549744},{"id":"https://openalex.org/C4792198","wikidata":"https://www.wikidata.org/wiki/Q1165944","display_name":"Land use","level":2,"score":0.1581314206123352},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.3390/rs11050523","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs11050523","pdf_url":"https://www.mdpi.com/2072-4292/11/5/523/pdf?version=1551870276","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1811.10166","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1811.10166","pdf_url":"https://arxiv.org/pdf/1811.10166","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:monash.edu:publications/69a5c559-400e-4399-a400-d255fddd3e49","is_oa":true,"landing_page_url":"https://research.monash.edu/en/publications/69a5c559-400e-4399-a400-d255fddd3e49","pdf_url":"https://researchmgt.monash.edu/ws/files/277543330/270013289_oa.pdf","source":{"id":"https://openalex.org/S4306402625","display_name":"Monash University Research Portal (Monash University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I56590836","host_organization_name":"Monash University","host_organization_lineage":["https://openalex.org/I56590836"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Pelletier, C, Webb, G I & Petitjean, F 2019, 'Temporal Convolutional Neural Network for the classification of satellite image time series', Remote Sensing, vol. 11, no. 5, 523. https://doi.org/10.3390/rs11050523","raw_type":"article"},{"id":"mag:2900573306","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/1811.10166","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"pmh:oai:doaj.org/article:745e7049666f4beca0bcbea576c11c8d","is_oa":true,"landing_page_url":"https://doaj.org/article/745e7049666f4beca0bcbea576c11c8d","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 11, Iss 5, p 523 (2019)","raw_type":"article"},{"id":"doi:10.48550/arxiv.1811.10166","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1811.10166","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/rs11050523","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs11050523","pdf_url":"https://www.mdpi.com/2072-4292/11/5/523/pdf?version=1551870276","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15","score":0.75}],"awards":[{"id":"https://openalex.org/G3124033015","display_name":null,"funder_award_id":"DE170100037","funder_id":"https://openalex.org/F4320334704","funder_display_name":"Australian Research Council"},{"id":"https://openalex.org/G4024461986","display_name":null,"funder_award_id":"FA2386-18-1-4030","funder_id":"https://openalex.org/F4320338279","funder_display_name":"Air Force Office of Scientific Research"}],"funders":[{"id":"https://openalex.org/F4320334704","display_name":"Australian Research Council","ror":"https://ror.org/05mmh0f86"},{"id":"https://openalex.org/F4320338279","display_name":"Air Force Office of Scientific Research","ror":"https://ror.org/011e9bt93"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2900573306.pdf","grobid_xml":"https://content.openalex.org/works/W2900573306.grobid-xml"},"referenced_works_count":94,"referenced_works":["https://openalex.org/W60686164","https://openalex.org/W1562291184","https://openalex.org/W1662323679","https://openalex.org/W1836465849","https://openalex.org/W1974289021","https://openalex.org/W2029185882","https://openalex.org/W2042645898","https://openalex.org/W2055248879","https://openalex.org/W2056435747","https://openalex.org/W2058947207","https://openalex.org/W2077509829","https://openalex.org/W2095705004","https://openalex.org/W2096733369","https://openalex.org/W2097054682","https://openalex.org/W2097998348","https://openalex.org/W2098676252","https://openalex.org/W2118037698","https://openalex.org/W2118899651","https://openalex.org/W2131241448","https://openalex.org/W2133564696","https://openalex.org/W2140190241","https://openalex.org/W2154579312","https://openalex.org/W2161565164","https://openalex.org/W2162931300","https://openalex.org/W2163605009","https://openalex.org/W2163922914","https://openalex.org/W2194775991","https://openalex.org/W2229287017","https://openalex.org/W2257669061","https://openalex.org/W2261059368","https://openalex.org/W2273708466","https://openalex.org/W2283002322","https://openalex.org/W2307094448","https://openalex.org/W2344186514","https://openalex.org/W2402144811","https://openalex.org/W2431738724","https://openalex.org/W2462592242","https://openalex.org/W2494341560","https://openalex.org/W2531168480","https://openalex.org/W2538244214","https://openalex.org/W2548003659","https://openalex.org/W2551393996","https://openalex.org/W2555077524","https://openalex.org/W2570343428","https://openalex.org/W2572303978","https://openalex.org/W2581906016","https://openalex.org/W2589453516","https://openalex.org/W2604086375","https://openalex.org/W2606788270","https://openalex.org/W2613718673","https://openalex.org/W2620572990","https://openalex.org/W2737391801","https://openalex.org/W2742706476","https://openalex.org/W2742878349","https://openalex.org/W2764034829","https://openalex.org/W2767953525","https://openalex.org/W2768064233","https://openalex.org/W2778936354","https://openalex.org/W2782522152","https://openalex.org/W2783608381","https://openalex.org/W2786038065","https://openalex.org/W2788008270","https://openalex.org/W2789676998","https://openalex.org/W2790063226","https://openalex.org/W2792827505","https://openalex.org/W2808098982","https://openalex.org/W2883026662","https://openalex.org/W2886493749","https://openalex.org/W2892035503","https://openalex.org/W2896998982","https://openalex.org/W2897656581","https://openalex.org/W2898843852","https://openalex.org/W2899125955","https://openalex.org/W2900059511","https://openalex.org/W2903282641","https://openalex.org/W2911964244","https://openalex.org/W2912934387","https://openalex.org/W2950220847","https://openalex.org/W2964121744","https://openalex.org/W2964308564","https://openalex.org/W3099206234","https://openalex.org/W3103964896","https://openalex.org/W3104839310","https://openalex.org/W3105127913","https://openalex.org/W3105357426","https://openalex.org/W3137695714","https://openalex.org/W4212883601","https://openalex.org/W6631190155","https://openalex.org/W6636950212","https://openalex.org/W6674330103","https://openalex.org/W6674385629","https://openalex.org/W6713134421","https://openalex.org/W6753602705","https://openalex.org/W6755893616"],"related_works":["https://openalex.org/W2963131120","https://openalex.org/W3175980645","https://openalex.org/W2773684780","https://openalex.org/W2986398450","https://openalex.org/W2085992718","https://openalex.org/W3078943193","https://openalex.org/W3192834253","https://openalex.org/W3197360656","https://openalex.org/W3173358151","https://openalex.org/W3049044367","https://openalex.org/W3104839310","https://openalex.org/W3187063439","https://openalex.org/W2742982421","https://openalex.org/W3185030868","https://openalex.org/W2795656559","https://openalex.org/W3199644418","https://openalex.org/W2992395948","https://openalex.org/W2955034228","https://openalex.org/W3206197202","https://openalex.org/W2811244448"],"abstract_inverted_index":{"Latest":[0],"remote":[1],"sensing":[2],"sensors":[3],"are":[4,23,188],"capable":[5],"of":[6,17,27,40,91,101,129,140,195,242],"acquiring":[7],"high":[8,49],"spatial":[9,53],"and":[10,35,52,135,149,176,213],"spectral":[11,51],"Satellite":[12],"Image":[13],"Time":[14],"Series":[15],"(SITS)":[16],"the":[18,41,89,92,115,138,192,196,207,239,243],"world.":[19],"These":[20],"image":[21],"series":[22],"a":[24,98,107],"key":[25],"component":[26],"classification":[28,66],"systems":[29],"that":[30,159,186],"aim":[31],"at":[32],"obtaining":[33],"up-to-date":[34],"accurate":[36,190],"land":[37,79,244],"cover":[38,80,245],"maps":[39,81,246],"Earth\u2019s":[42],"surfaces.":[43],"More":[44],"specifically,":[45],"current":[46,193],"SITS":[47,143,199],"combine":[48],"temporal,":[50],"resolutions,":[54],"which":[55,111],"makes":[56],"it":[57],"possible":[58],"to":[59,77,120,133,147,163],"closely":[60],"monitor":[61],"vegetation":[62],"dynamics.":[63],"Although":[64],"traditional":[65],"algorithms,":[67],"such":[68,216],"as":[69,145,217],"Random":[70],"Forest":[71],"(RF),":[72],"have":[73],"been":[74],"successfully":[75],"applied":[76],"create":[78],"from":[82],"SITS,":[83],"these":[84],"algorithms":[85],"do":[86],"not":[87],"make":[88],"most":[90],"temporal":[93,116,123,164],"domain.":[94],"This":[95],"paper":[96,131],"proposes":[97],"comprehensive":[99],"study":[100],"Temporal":[102],"Convolutional":[103],"Neural":[104,151],"Networks":[105,152],"(TempCNNs),":[106],"deep":[108,156],"learning":[109,157],"approach":[110,158],"applies":[112],"convolutions":[113],"in":[114,118,229],"dimension":[117],"order":[119],"automatically":[121],"learn":[122],"(and":[124],"spectral)":[125],"features.":[126],"The":[127,182],"goal":[128],"this":[130],"is":[132,160],"quantitatively":[134],"qualitatively":[136],"evaluate":[137],"contribution":[139],"TempCNNs":[141,187],"for":[142,198],"classification,":[144],"compared":[146],"RF":[148],"Recurrent":[150],"(RNNs)":[153],"\u2014a":[154],"standard":[155,227],"particularly":[161],"suited":[162],"data.":[165],"We":[166,201],"carry":[167],"out":[168,223],"experiments":[169],"on":[170,206],"Formosat-2":[171],"scene":[172],"with":[173,226],"46":[174],"images":[175],"one":[177],"million":[178],"labelled":[179],"time":[180],"series.":[181],"experimental":[183],"results":[184,228],"show":[185],"more":[189],"than":[191],"state":[194],"art":[197],"classification.":[200],"provide":[202],"some":[203,224],"general":[204],"guidelines":[205],"network":[208],"architecture,":[209],"common":[210],"regularization":[211],"mechanisms,":[212],"hyper-parameter":[214],"values":[215],"batch":[218],"size;":[219],"we":[220,237],"also":[221],"draw":[222],"differences":[225],"computer":[230],"vision":[231],"(e.g.,":[232],"about":[233],"pooling":[234],"layers).":[235],"Finally,":[236],"assess":[238],"visual":[240],"quality":[241],"produced":[247],"by":[248],"TempCNNs.":[249]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":12},{"year":2019,"cited_by_count":1}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2019-07-30T00:00:00"}