{"id":"https://openalex.org/W4413158587","doi":"https://doi.org/10.1109/wetice67341.2025.11092212","title":"YOLO-based Recognition of some Crop Categories from Real-World Aerial Images","display_name":"YOLO-based Recognition of some Crop Categories from Real-World Aerial Images","publication_year":2025,"publication_date":"2025-07-23","ids":{"openalex":"https://openalex.org/W4413158587","doi":"https://doi.org/10.1109/wetice67341.2025.11092212"},"language":"en","primary_location":{"id":"doi:10.1109/wetice67341.2025.11092212","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wetice67341.2025.11092212","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 33rd International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)","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/A5083644845","display_name":"Salvatore Calcagno","orcid":"https://orcid.org/0000-0001-7128-9663"},"institutions":[{"id":"https://openalex.org/I39063666","display_name":"University of Catania","ror":"https://ror.org/03a64bh57","country_code":"IT","type":"education","lineage":["https://openalex.org/I39063666"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Salvatore Calcagno","raw_affiliation_strings":["University of Catania,Dipartimento di Matematica e Informatica,Catania,Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Catania,Dipartimento di Matematica e Informatica,Catania,Italy","institution_ids":["https://openalex.org/I39063666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119285279","display_name":"Erika Scaletta","orcid":"https://orcid.org/0009-0003-3692-6091"},"institutions":[{"id":"https://openalex.org/I39063666","display_name":"University of Catania","ror":"https://ror.org/03a64bh57","country_code":"IT","type":"education","lineage":["https://openalex.org/I39063666"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Erika Scaletta","raw_affiliation_strings":["University of Catania,Dipartimento di Matematica e Informatica,Catania,Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Catania,Dipartimento di Matematica e Informatica,Catania,Italy","institution_ids":["https://openalex.org/I39063666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011707033","display_name":"Emiliano Tramontana","orcid":"https://orcid.org/0000-0002-7169-659X"},"institutions":[{"id":"https://openalex.org/I39063666","display_name":"University of Catania","ror":"https://ror.org/03a64bh57","country_code":"IT","type":"education","lineage":["https://openalex.org/I39063666"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Emiliano Tramontana","raw_affiliation_strings":["University of Catania,Dipartimento di Matematica e Informatica,Catania,Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Catania,Dipartimento di Matematica e Informatica,Catania,Italy","institution_ids":["https://openalex.org/I39063666"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082619241","display_name":"Gabriella Verga","orcid":"https://orcid.org/0009-0007-1028-2178"},"institutions":[{"id":"https://openalex.org/I39063666","display_name":"University of Catania","ror":"https://ror.org/03a64bh57","country_code":"IT","type":"education","lineage":["https://openalex.org/I39063666"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Gabriella Verga","raw_affiliation_strings":["University of Catania,Dipartimento di Matematica e Informatica,Catania,Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Catania,Dipartimento di Matematica e Informatica,Catania,Italy","institution_ids":["https://openalex.org/I39063666"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I39063666"],"apc_list":null,"apc_paid":null,"fwci":1.1602,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.82185152,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9088000059127808,"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"}},"topics":[{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9088000059127808,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9017999768257141,"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/computer-science","display_name":"Computer science","score":0.6028929948806763},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5610874891281128},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.490831196308136},{"id":"https://openalex.org/keywords/crop","display_name":"Crop","score":0.4543752372264862},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3539320230484009},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32840198278427124},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.24846938252449036},{"id":"https://openalex.org/keywords/forestry","display_name":"Forestry","score":0.08372780680656433}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6028929948806763},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5610874891281128},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.490831196308136},{"id":"https://openalex.org/C137580998","wikidata":"https://www.wikidata.org/wiki/Q235352","display_name":"Crop","level":2,"score":0.4543752372264862},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3539320230484009},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32840198278427124},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.24846938252449036},{"id":"https://openalex.org/C97137747","wikidata":"https://www.wikidata.org/wiki/Q38112","display_name":"Forestry","level":1,"score":0.08372780680656433}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wetice67341.2025.11092212","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wetice67341.2025.11092212","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 33rd International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2","score":0.7599999904632568}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"The":[0,84],"analysis":[1],"of":[2,8,41,81,86,111],"aerial":[3],"images":[4],"to":[5,36,75,127],"detect":[6],"objects":[7],"interest":[9],"is":[10],"an":[11,66],"active":[12],"research":[13],"field":[14],"as":[15,46,48,54,123],"its":[16],"results":[17],"can":[18,99,120],"be":[19,100,121],"very":[20,101],"useful":[21,102],"for":[22],"planning":[23],"crops,":[24],"estimating":[25],"gains":[26],"and":[27,56,73,79,106],"costs,":[28],"etc.":[29],"This":[30],"paper":[31],"proposes":[32],"a":[33,44,124],"novel":[34],"way":[35],"distinguish":[37],"among":[38],"some":[39],"categories":[40],"crops":[42],"in":[43,103],"field,":[45],"well":[47],"parts":[49],"representing":[50],"man-made":[51],"objects,":[52],"such":[53],"roads":[55],"buildings.":[57],"For":[58],"this,":[59],"advanced":[60],"YOLO":[61,90],"models":[62],"were":[63],"trained":[64,89,97],"using":[65],"accurately":[67],"labeled":[68,116],"data":[69,118],"set,":[70],"then":[71],"validated":[72],"tested":[74],"assess":[76],"the":[77,82,87,96,109,114],"accuracy":[78],"precision":[80],"detection.":[83],"outcome":[85],"best":[88],"model":[91,98],"shows":[92],"high":[93],"precision.":[94],"Therefore,":[95],"scanning":[104],"areas":[105],"systematically":[107],"detecting":[108],"state":[110],"crops.":[112],"Moreover,":[113],"high-quality":[115],"image":[117],"set":[119,126],"used":[122],"reference":[125],"test":[128],"other":[129],"approaches.":[130]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}