{"id":"https://openalex.org/W4285601290","doi":"https://doi.org/10.24963/ijcai.2022/703","title":"Monitoring Vegetation From Space at Extremely Fine Resolutions via Coarsely-Supervised Smooth U-Net","display_name":"Monitoring Vegetation From Space at Extremely Fine Resolutions via Coarsely-Supervised Smooth U-Net","publication_year":2022,"publication_date":"2022-07-01","ids":{"openalex":"https://openalex.org/W4285601290","doi":"https://doi.org/10.24963/ijcai.2022/703"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2022/703","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2022/703","pdf_url":"https://www.ijcai.org/proceedings/2022/0703.pdf","source":{"id":"https://openalex.org/S4363608755","display_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://www.ijcai.org/proceedings/2022/0703.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5064695038","display_name":"Joshua Fan","orcid":"https://orcid.org/0000-0002-8525-0222"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Joshua Fan","raw_affiliation_strings":["Cornell University, Ithaca, NY","Department of Computer Science, Cornell University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cornell University, Ithaca, NY","institution_ids":["https://openalex.org/I205783295"]},{"raw_affiliation_string":"Department of Computer Science, Cornell University","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100368475","display_name":"Di Chen","orcid":"https://orcid.org/0009-0004-1791-2302"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Di Chen","raw_affiliation_strings":["Cornell University, Ithaca, NY","Department of Computer Science, Cornell University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cornell University, Ithaca, NY","institution_ids":["https://openalex.org/I205783295"]},{"raw_affiliation_string":"Department of Computer Science, Cornell University","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038065287","display_name":"Jiaming Wen","orcid":"https://orcid.org/0000-0001-9840-0720"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiaming Wen","raw_affiliation_strings":["Cornell University, Ithaca, NY","School of Integrative Plant Science -Soil and Crop Sciences Section, Cornell University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cornell University, Ithaca, NY","institution_ids":["https://openalex.org/I205783295"]},{"raw_affiliation_string":"School of Integrative Plant Science -Soil and Crop Sciences Section, Cornell University","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011092289","display_name":"Ying Sun","orcid":"https://orcid.org/0000-0002-9819-1241"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ying Sun","raw_affiliation_strings":["Cornell University, Ithaca, NY","School of Integrative Plant Science -Soil and Crop Sciences Section, Cornell University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cornell University, Ithaca, NY","institution_ids":["https://openalex.org/I205783295"]},{"raw_affiliation_string":"School of Integrative Plant Science -Soil and Crop Sciences Section, Cornell University","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073645419","display_name":"Carla Gomes","orcid":"https://orcid.org/0000-0002-6089-0485"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Carla Gomes","raw_affiliation_strings":["Cornell University, Ithaca, NY","Department of Computer Science, Cornell University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cornell University, Ithaca, NY","institution_ids":["https://openalex.org/I205783295"]},{"raw_affiliation_string":"Department of Computer Science, Cornell University","institution_ids":["https://openalex.org/I205783295"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5073645419"],"corresponding_institution_ids":["https://openalex.org/I205783295"],"apc_list":null,"apc_paid":null,"fwci":0.7252,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.62322473,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"5066","last_page":"5072"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9976999759674072,"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"}},{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.9930999875068665,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.7280368208885193},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6109883189201355},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.528563380241394},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5175554156303406},{"id":"https://openalex.org/keywords/downscaling","display_name":"Downscaling","score":0.5129306316375732},{"id":"https://openalex.org/keywords/crop-productivity","display_name":"Crop productivity","score":0.4733840525150299},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4463709890842438},{"id":"https://openalex.org/keywords/vegetation","display_name":"Vegetation (pathology)","score":0.44318336248397827},{"id":"https://openalex.org/keywords/elastic-net-regularization","display_name":"Elastic net regularization","score":0.4302743077278137},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.4277839660644531},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4043659567832947},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3994206190109253},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.37142205238342285},{"id":"https://openalex.org/keywords/agriculture","display_name":"Agriculture","score":0.3081241548061371},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.1521521508693695},{"id":"https://openalex.org/keywords/precipitation","display_name":"Precipitation","score":0.13524654507637024},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.12773022055625916},{"id":"https://openalex.org/keywords/ecology","display_name":"Ecology","score":0.11464226245880127},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.09685739874839783},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.09227427840232849}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.7280368208885193},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6109883189201355},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.528563380241394},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5175554156303406},{"id":"https://openalex.org/C41156917","wikidata":"https://www.wikidata.org/wiki/Q682831","display_name":"Downscaling","level":3,"score":0.5129306316375732},{"id":"https://openalex.org/C2993120057","wikidata":"https://www.wikidata.org/wiki/Q3816336","display_name":"Crop productivity","level":3,"score":0.4733840525150299},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4463709890842438},{"id":"https://openalex.org/C2776133958","wikidata":"https://www.wikidata.org/wiki/Q7918366","display_name":"Vegetation (pathology)","level":2,"score":0.44318336248397827},{"id":"https://openalex.org/C203868755","wikidata":"https://www.wikidata.org/wiki/Q5353562","display_name":"Elastic net regularization","level":3,"score":0.4302743077278137},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.4277839660644531},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4043659567832947},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3994206190109253},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.37142205238342285},{"id":"https://openalex.org/C118518473","wikidata":"https://www.wikidata.org/wiki/Q11451","display_name":"Agriculture","level":2,"score":0.3081241548061371},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.1521521508693695},{"id":"https://openalex.org/C107054158","wikidata":"https://www.wikidata.org/wiki/Q25257","display_name":"Precipitation","level":2,"score":0.13524654507637024},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.12773022055625916},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.11464226245880127},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.09685739874839783},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.09227427840232849},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.0},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","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":1,"locations":[{"id":"doi:10.24963/ijcai.2022/703","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2022/703","pdf_url":"https://www.ijcai.org/proceedings/2022/0703.pdf","source":{"id":"https://openalex.org/S4363608755","display_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2022/703","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2022/703","pdf_url":"https://www.ijcai.org/proceedings/2022/0703.pdf","source":{"id":"https://openalex.org/S4363608755","display_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2398348521","display_name":"NRT-HDR: Team training to develop new hardware and software applications for digital plant science across multiple scales","funder_award_id":"1922551","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8626354529","display_name":null,"funder_award_id":"CCF-1522054","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4285601290.pdf","grobid_xml":"https://content.openalex.org/works/W4285601290.grobid-xml"},"referenced_works_count":20,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2055695879","https://openalex.org/W2067624665","https://openalex.org/W2103284199","https://openalex.org/W2139198479","https://openalex.org/W2599868771","https://openalex.org/W2604548710","https://openalex.org/W2762155383","https://openalex.org/W2908510526","https://openalex.org/W2911777435","https://openalex.org/W2919558946","https://openalex.org/W2963004790","https://openalex.org/W3000627240","https://openalex.org/W3001646307","https://openalex.org/W3002315818","https://openalex.org/W3017707823","https://openalex.org/W3091807257","https://openalex.org/W3149699174","https://openalex.org/W4250528530","https://openalex.org/W4287815109"],"related_works":["https://openalex.org/W2394436593","https://openalex.org/W4362597605","https://openalex.org/W3013458534","https://openalex.org/W1574414179","https://openalex.org/W4297676672","https://openalex.org/W3009056573","https://openalex.org/W3010558748","https://openalex.org/W2922073769","https://openalex.org/W4386972620","https://openalex.org/W3033173380"],"abstract_inverted_index":{"Monitoring":[0],"vegetation":[1],"productivity":[2,37],"at":[3,47,74,82,93],"extremely":[4],"fine":[5],"resolutions":[6,97],"is":[7,118],"valuable":[8],"for":[9,132,162],"real-world":[10],"agricultural":[11],"applications,":[12],"such":[13],"as":[14,155],"detecting":[15],"crop":[16,59],"stress":[17],"and":[18,116],"providing":[19],"early":[20],"warning":[21],"of":[22,142],"food":[23],"insecurity.":[24],"Solar-Induced":[25],"Chlorophyll":[26],"Fluorescence":[27],"(SIF)":[28],"provides":[29],"a":[30,48,67,83,100,129,156],"promising":[31],"way":[32],"to":[33,55,90],"directly":[34],"measure":[35],"plant":[36],"from":[38],"space.":[39],"However,":[40],"satellite":[41],"SIF":[42,80,92,117,173],"observations":[43],"are":[44,63,160],"only":[45,78],"available":[46],"coarse":[49,84,134],"spatial":[50,96],"resolution,":[51],"making":[52],"it":[53],"impossible":[54],"monitor":[56],"how":[57],"individual":[58],"types":[60],"or":[61],"farms":[62],"doing.":[64],"This":[65],"poses":[66],"challenging":[68],"coarsely-supervised":[69],"regression":[70],"(or":[71],"downscaling)":[72],"task;":[73],"training":[75],"time,":[76],"we":[77,88,123],"have":[79,105],"labels":[81],"resolution":[85],"(3km),":[86],"but":[87,110],"want":[89],"predict":[91],"much":[94],"finer":[95],"(e.g.":[98],"30m,":[99],"100x":[101],"increase).":[102],"We":[103],"also":[104],"additional":[106],"fine-resolution":[107],"input":[108],"features,":[109],"the":[111,139],"relationship":[112],"between":[113],"these":[114],"features":[115],"unknown.":[119],"To":[120],"address":[121],"this,":[122],"propose":[124],"Coarsely-Supervised":[125],"Smooth":[126],"U-Net":[127],"(CS-SUNet),":[128],"novel":[130,147],"method":[131],"this":[133],"supervision":[135],"setting.":[136],"CS-SUNet":[137,168],"combines":[138],"expressive":[140],"power":[141],"deep":[143],"convolutional":[144],"networks":[145],"with":[146],"regularization":[148],"methods":[149],"based":[150],"on":[151],"prior":[152],"knowledge":[153],"(such":[154],"smoothness":[157],"loss)":[158],"that":[159,167],"crucial":[161],"preventing":[163],"overfitting.":[164],"Experiments":[165],"show":[166],"resolves":[169],"fine-grained":[170],"variations":[171],"in":[172],"more":[174],"accurately":[175],"than":[176],"existing":[177],"methods.":[178]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-22T08:00:12.763002","created_date":"2025-10-10T00:00:00"}