{"id":"https://openalex.org/W4292830010","doi":"https://doi.org/10.1109/agro-geoinformatics55649.2022.9858952","title":"Delineation of agricultural fields using Psi-Net from high-resolution remote sensing images","display_name":"Delineation of agricultural fields using Psi-Net from high-resolution remote sensing images","publication_year":2022,"publication_date":"2022-07-11","ids":{"openalex":"https://openalex.org/W4292830010","doi":"https://doi.org/10.1109/agro-geoinformatics55649.2022.9858952"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/agro-geoinformatics55649.2022.9858952","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5101521809","display_name":"Long Jiang","orcid":"https://orcid.org/0000-0003-1969-0980"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiang Long","raw_affiliation_strings":["The Academy of Digital China (Fujian), Fuzhou University, Fuzhou, China"],"affiliations":[{"raw_affiliation_string":"The Academy of Digital China (Fujian), Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100348210","display_name":"Mengmeng Li","orcid":"https://orcid.org/0000-0002-9083-0475"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengmeng Li","raw_affiliation_strings":["The Academy of Digital China (Fujian), Fuzhou University, Fuzhou, China"],"affiliations":[{"raw_affiliation_string":"The Academy of Digital China (Fujian), Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006063367","display_name":"Mingxing Cha","orcid":"https://orcid.org/0009-0005-3890-3832"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingxing Cha","raw_affiliation_strings":["The Academy of Digital China (Fujian), Fuzhou University, Fuzhou, China"],"affiliations":[{"raw_affiliation_string":"The Academy of Digital China (Fujian), Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100403891","display_name":"Xiaoqin Wang","orcid":"https://orcid.org/0000-0002-3796-321X"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoqin Wang","raw_affiliation_strings":["The Academy of Digital China (Fujian), Fuzhou University, Fuzhou, China"],"affiliations":[{"raw_affiliation_string":"The Academy of Digital China (Fujian), Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060016795","display_name":"Heng Huang","orcid":"https://orcid.org/0000-0002-3483-8333"},"institutions":[],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Heng Huang","raw_affiliation_strings":["Fujian Geologic Surveying and Mapping Institute, Fuzhou, China"],"affiliations":[{"raw_affiliation_string":"Fujian Geologic Surveying and Mapping Institute, Fuzhou, China","institution_ids":[]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.186,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.427994,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":60,"max":70},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9978,"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":0.9978,"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":0.9969,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9967,"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/net","display_name":"Net (polyhedron)","score":0.46967608}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.746639},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6947057},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6372471},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6323194},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5360636},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5114564},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5100742},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.4903281},{"id":"https://openalex.org/C14166107","wikidata":"https://www.wikidata.org/wiki/Q253829","display_name":"Net (polyhedron)","level":2,"score":0.46967608},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44864967},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.43061167},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.42594635},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3826385},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37182269},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13912842},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.13498348},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","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}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/agro-geoinformatics55649.2022.9858952","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2","score":0.72}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":11,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2033275961","https://openalex.org/W2195004773","https://openalex.org/W2395611524","https://openalex.org/W2727536798","https://openalex.org/W2735833004","https://openalex.org/W2806070179","https://openalex.org/W2979600871","https://openalex.org/W3040196063","https://openalex.org/W4241071816","https://openalex.org/W845365781"],"related_works":["https://openalex.org/W2739874619","https://openalex.org/W2159066190","https://openalex.org/W2122581818","https://openalex.org/W2117933325","https://openalex.org/W2117664411","https://openalex.org/W2110230079","https://openalex.org/W1967061043","https://openalex.org/W1721780360","https://openalex.org/W1669643531","https://openalex.org/W1507266234"],"abstract_inverted_index":{"Boundary":[0],"information":[1],"of":[2,21,30,59,63,127,132,138,171],"agricultural":[3,9,31,130],"fields":[4],"is":[5],"essential":[6],"to":[7,26,52,76,99,104],"many":[8],"applications,":[10],"particularly":[11],"at":[12],"the":[13,19,28,35,54,101,124,128,136,139,157,165,169,179],"field":[14,189],"level.":[15],"This":[16],"paper":[17],"investigates":[18],"use":[20,44],"high-resolution":[22,192],"remote":[23,193],"sensing":[24,194],"images":[25],"delineate":[27],"boundaries":[29,190],"fields.":[32],"We":[33,112,176],"consider":[34],"delineation":[36],"task":[37,79,148],"a":[38,45,60,77,106,116,184],"multi-task":[39],"semantic":[40,55,149],"segmentation":[41,150],"problem":[42],"and":[43,66,83,90,173],"recent":[46],"deep":[47],"neural":[48],"network,":[49],"i.e.,":[50],"Psi-Net,":[51],"do":[53],"segmentation.":[56],"The":[57,69,94],"structure":[58],"Psi-Net":[61,161,181],"consists":[62],"an":[64],"encoder":[65],"three":[67,72],"decoders.":[68],"decoders":[70],"learn":[71],"parallel":[73],"tasks,":[74],"corresponding":[75],"primary":[78],"(i.e.,":[80,87],"mask":[81,102,108],"prediction)":[82],"two":[84],"additional":[85,95],"tasks":[86,96],"contour":[88],"detection":[89],"distance":[91],"map":[92],"estimation).":[93],"are":[97],"used":[98],"regularize":[100],"prediction":[103],"produce":[105],"refined":[107],"with":[109,145],"smooth":[110],"boundaries.":[111],"conducted":[113],"experiments":[114],"on":[115],"GF1":[117],"PMS":[118],"satellite":[119],"image":[120],"(2m)":[121],"acquired":[122],"in":[123],"21st":[125],"regiment":[126],"2nd":[129],"division":[131],"Xinjiang.":[133],"To":[134],"evaluate":[135],"effectiveness":[137],"proposed":[140,158,180],"method,":[141],"we":[142],"compared":[143],"it":[144],"existing":[146,166],"single":[147],"using":[151,160],"UNet.":[152],"Our":[153],"results":[154],"show":[155],"that":[156,178],"method":[159,167,182],"performed":[162],"better":[163],"than":[164],"from":[168,191],"perspective":[170],"geometric":[172],"attribute":[174],"accuracies.":[175],"conclude":[177],"has":[183],"high":[185],"potential":[186],"for":[187],"extracting":[188],"images.":[195]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4292830010","counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2024-12-12T01:14:16.417342","created_date":"2022-08-24"}