{"id":"https://openalex.org/W4416184285","doi":"https://doi.org/10.1109/sibgrapi67909.2025.11223377","title":"A Study of Synthetic and Cross-Domain Real-Data Pre-Training for Aerial Farm Monitoring","display_name":"A Study of Synthetic and Cross-Domain Real-Data Pre-Training for Aerial Farm Monitoring","publication_year":2025,"publication_date":"2025-09-30","ids":{"openalex":"https://openalex.org/W4416184285","doi":"https://doi.org/10.1109/sibgrapi67909.2025.11223377"},"language":null,"primary_location":{"id":"doi:10.1109/sibgrapi67909.2025.11223377","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sibgrapi67909.2025.11223377","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 38th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)","raw_type":"proceedings-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/A5083104856","display_name":"Juliana Barros Ferreira","orcid":"https://orcid.org/0000-0001-7790-5551"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Juliana Ferreira","raw_affiliation_strings":["Universidade Federal de Viçosa - UFV,Department of Informatics,Viçosa,Brazil"],"affiliations":[{"raw_affiliation_string":"Universidade Federal de Viçosa - UFV,Department of Informatics,Viçosa,Brazil","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008446448","display_name":"Lucas Cruz da Silva","orcid":"https://orcid.org/0000-0002-9184-3710"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lucas Silva","raw_affiliation_strings":["Universidade Federal de Viçosa - UFV,Department of Informatics,Viçosa,Brazil"],"affiliations":[{"raw_affiliation_string":"Universidade Federal de Viçosa - UFV,Department of Informatics,Viçosa,Brazil","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023592035","display_name":"Ant\u00f4nio Tadeu A. Gomes","orcid":"https://orcid.org/0000-0002-0746-4014"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ant\u00f4nio Gomes","raw_affiliation_strings":["Universidade Federal de Viçosa - UFV,Department of Informatics,Viçosa,Brazil"],"affiliations":[{"raw_affiliation_string":"Universidade Federal de Viçosa - UFV,Department of Informatics,Viçosa,Brazil","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090987423","display_name":"Larissa Ferreira Rodrigues Moreira","orcid":"https://orcid.org/0000-0001-8947-9182"},"institutions":[{"id":"https://openalex.org/I1283613182","display_name":"Universidade Tecnol\u00f3gica Federal do Paran\u00e1","ror":"https://ror.org/002v2kq79","country_code":"BR","type":"education","lineage":["https://openalex.org/I1283613182"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Larissa Rodrigues","raw_affiliation_strings":["Institute of Exacts and Technological Sciences, Universidade Federal de Viçosa - UFV,Rio Paranaíba,Brazil"],"affiliations":[{"raw_affiliation_string":"Institute of Exacts and Technological Sciences, Universidade Federal de Viçosa - UFV,Rio Paranaíba,Brazil","institution_ids":["https://openalex.org/I1283613182"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102859185","display_name":"Thiago Ferreira Gomes","orcid":"https://orcid.org/0009-0006-1259-846X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Thiago Gomes","raw_affiliation_strings":["Universidade Federal de Viçosa - UFV,Department of Informatics,Viçosa,Brazil"],"affiliations":[{"raw_affiliation_string":"Universidade Federal de Viçosa - UFV,Department of Informatics,Viçosa,Brazil","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090596227","display_name":"Michel M. Silva","orcid":"https://orcid.org/0000-0002-2499-9619"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Michel Silva","raw_affiliation_strings":["Universidade Federal de Viçosa - UFV,Department of Informatics,Viçosa,Brazil"],"affiliations":[{"raw_affiliation_string":"Universidade Federal de Viçosa - UFV,Department of Informatics,Viçosa,Brazil","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5083104856"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.32040966,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.2393999993801117,"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":0.2393999993801117,"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/T10616","display_name":"Smart Agriculture and AI","score":0.19300000369548798,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11133","display_name":"UAV Applications and Optimization","score":0.1428000032901764,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.7620999813079834},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6579999923706055},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.525600016117096},{"id":"https://openalex.org/keywords/aerial-survey","display_name":"Aerial survey","score":0.4129999876022339},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.41040000319480896},{"id":"https://openalex.org/keywords/aerial-image","display_name":"Aerial image","score":0.38760000467300415},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.36890000104904175},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.3555000126361847}],"concepts":[{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.7620999813079834},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6579999923706055},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5630999803543091},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.525600016117096},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.47110000252723694},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4620000123977661},{"id":"https://openalex.org/C176262533","wikidata":"https://www.wikidata.org/wiki/Q4688034","display_name":"Aerial survey","level":2,"score":0.4129999876022339},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.41040000319480896},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.38760000467300415},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.36890000104904175},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3555000126361847},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3540000021457672},{"id":"https://openalex.org/C2987819851","wikidata":"https://www.wikidata.org/wiki/Q191839","display_name":"Aerial imagery","level":2,"score":0.3483000099658966},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3441999852657318},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.3361999988555908},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.298799991607666},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.29010000824928284},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.27900001406669617},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.27790001034736633},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.2685000002384186},{"id":"https://openalex.org/C120217122","wikidata":"https://www.wikidata.org/wiki/Q740083","display_name":"Precision agriculture","level":3,"score":0.2628999948501587},{"id":"https://openalex.org/C59519942","wikidata":"https://www.wikidata.org/wiki/Q650665","display_name":"Drone","level":2,"score":0.2623000144958496},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2603999972343445},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.2596000134944916}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/sibgrapi67909.2025.11223377","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sibgrapi67909.2025.11223377","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 38th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W3014641072","https://openalex.org/W3089769990","https://openalex.org/W3109301572","https://openalex.org/W4281677710","https://openalex.org/W4392248351","https://openalex.org/W4401531838","https://openalex.org/W4402811401","https://openalex.org/W4403492139","https://openalex.org/W4405362857","https://openalex.org/W4406563935","https://openalex.org/W4410731805"],"related_works":[],"abstract_inverted_index":{"The":[0],"use":[1,61],"of":[2,41,55,62,122],"Unmanned":[3],"Aerial":[4],"Vehicles":[5],"(UAVs)":[6],"for":[7],"monitoring":[8],"farms":[9],"has":[10],"increased":[11],"in":[12,47,81,114,125,128,132],"recent":[13],"years.":[14],"Consequently,":[15],"it":[16],"is":[17],"essential":[18],"to":[19,24,119,136],"enhance":[20],"Artificial":[21],"Intelligence":[22],"capabilities":[23],"leverage":[25],"the":[26,48,53,60,70,109,115,137],"imagery":[27],"captured":[28],"by":[29],"these":[30],"devices":[31],"fully.":[32],"Training":[33],"semantic":[34],"segmentation":[35],"models":[36],"requires":[37],"a":[38,82,89],"large":[39],"number":[40],"labeled":[42],"images,":[43],"which":[44],"are":[45],"nonexistent":[46],"agricultural":[49],"context.":[50],"To":[51],"address":[52],"bottleneck":[54],"manual":[56],"labeling,":[57],"we":[58],"investigate":[59],"different":[63,91],"pre-training":[64,107,139],"strategies":[65],"utilizing":[66],"synthetic":[67],"data":[68,87],"from":[69,88],"same":[71],"domain":[72,92],"(Synthetic":[73],"Dataset),":[74,94],"e.g.,":[75,95],"UAV":[76],"flights":[77],"over":[78],"rural":[79],"areas":[80],"virtual":[83],"environment,":[84],"and":[85,102,130],"real":[86],"slightly":[90],"(Cross-Domain":[93],"high-resolution":[96],"remote":[97],"sensing":[98],"images.":[99],"Both":[100],"quantitative":[101],"qualitative":[103],"results":[104],"demonstrated":[105],"that":[106],"using":[108],"Synthetic":[110],"Dataset":[111],"performed":[112],"better":[113],"final":[116],"training,":[117],"leading":[118],"an":[120],"increase":[121],"3.1":[123],"p.p.":[124],"IoU,":[126],"6.4":[127],"F1-Score,":[129],"7.5":[131],"Recall":[133],"when":[134],"compared":[135],"Cross-Domain":[138],"strategy.":[140]},"counts_by_year":[],"updated_date":"2026-04-17T18:11:37.981687","created_date":"2025-11-11T00:00:00"}