{"id":"https://openalex.org/W6944663812","doi":"https://doi.org/10.18420/giljt2025_09","title":"Recognition of phenological development stages of apple blossoms using computer vision","display_name":"Recognition of phenological development stages of apple blossoms using computer vision","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W6944663812","doi":"https://doi.org/10.18420/giljt2025_09"},"language":"en","primary_location":{"id":"doi:10.18420/giljt2025_09","is_oa":true,"landing_page_url":"https://doi.org/10.18420/giljt2025_09","pdf_url":null,"source":{"id":"https://openalex.org/S7407052918","display_name":"Gesellschaft f\u00fcr Informatik (GI)","issn_l":null,"issn":[],"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":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.18420/giljt2025_09","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Xuan Khanh Nguyen, Bastian Braun","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Xuan Khanh Nguyen, Bastian Braun","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.55047266,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9458000063896179,"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":0.9458000063896179,"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/T11546","display_name":"Plant Physiology and Cultivation Studies","score":0.011800000444054604,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.008200000040233135,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.7192000150680542},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7188000082969666},{"id":"https://openalex.org/keywords/orchard","display_name":"Orchard","score":0.6115999817848206},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5960999727249146},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4032000005245209},{"id":"https://openalex.org/keywords/precision-agriculture","display_name":"Precision agriculture","score":0.4009000062942505},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.36250001192092896},{"id":"https://openalex.org/keywords/machine-vision","display_name":"Machine vision","score":0.33550000190734863}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.7192000150680542},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7188000082969666},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7148000001907349},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.626800000667572},{"id":"https://openalex.org/C2780753983","wikidata":"https://www.wikidata.org/wiki/Q236371","display_name":"Orchard","level":2,"score":0.6115999817848206},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5960999727249146},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5382999777793884},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4032000005245209},{"id":"https://openalex.org/C120217122","wikidata":"https://www.wikidata.org/wiki/Q740083","display_name":"Precision agriculture","level":3,"score":0.4009000062942505},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.36250001192092896},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33709999918937683},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.33550000190734863},{"id":"https://openalex.org/C51417038","wikidata":"https://www.wikidata.org/wiki/Q272737","display_name":"Phenology","level":2,"score":0.32109999656677246},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.31610000133514404},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.30239999294281006},{"id":"https://openalex.org/C77660652","wikidata":"https://www.wikidata.org/wiki/Q150971","display_name":"Computer graphics","level":2,"score":0.30140000581741333},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.29919999837875366},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2962999939918518},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2874999940395355},{"id":"https://openalex.org/C32198211","wikidata":"https://www.wikidata.org/wiki/Q165044","display_name":"Greenhouse","level":2,"score":0.2782000005245209},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.26080000400543213},{"id":"https://openalex.org/C36372059","wikidata":"https://www.wikidata.org/wiki/Q376492","display_name":"HSL and HSV","level":3,"score":0.25769999623298645},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.25279998779296875}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18420/giljt2025_09","is_oa":true,"landing_page_url":"https://doi.org/10.18420/giljt2025_09","pdf_url":null,"source":{"id":"https://openalex.org/S7407052918","display_name":"Gesellschaft f\u00fcr Informatik (GI)","issn_l":null,"issn":[],"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":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"doi:10.18420/giljt2025_09","is_oa":true,"landing_page_url":"https://doi.org/10.18420/giljt2025_09","pdf_url":null,"source":{"id":"https://openalex.org/S7407052918","display_name":"Gesellschaft f\u00fcr Informatik (GI)","issn_l":null,"issn":[],"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":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/2","score":0.7800592184066772,"display_name":"Zero hunger"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Deep":[0],"learning-based":[1],"computer":[2],"vision":[3],"is":[4],"increasingly":[5],"supporting":[6],"precision":[7],"agriculture":[8],"in":[9,40,131],"orchards,":[10],"reducing":[11],"reliance":[12],"on":[13,120],"manual":[14],"monitoring":[15,26],"by":[16],"trained":[17],"specialists.":[18],"This":[19],"work":[20],"presents":[21],"an":[22,32,46],"approach":[23],"for":[24,35,67,95,102],"automated":[25],"of":[27,49,90],"apple":[28,53],"blossom":[29,124],"growth":[30,68],"stages,":[31],"important":[33],"task":[34],"optimizing":[36],"yield":[37],"and":[38,71],"quality":[39],"orchard":[41,104],"management.":[42,105],"We":[43],"(1)":[44],"construct":[45],"annotated":[47],"dataset":[48],"hourly":[50],"images":[51],"capturing":[52],"blossoms":[54],"across":[55],"BBCH":[56],"stages":[57],"53":[58],"to":[59,80,126],"71,":[60],"(2)":[61],"develop":[62],"convolutional":[63],"neural":[64],"networks":[65],"(CNNs)":[66],"stage":[69],"classification,":[70],"(3)":[72],"validate":[73],"model":[74,85],"performance":[75],"using":[76],"explainable":[77],"AI":[78],"(XAI)":[79],"ensure":[81],"interpretability.":[82],"Our":[83],"best-performing":[84],"achieves":[86],"a":[87],"classification":[88],"accuracy":[89],"93.1%,":[91],"demonstrating":[92],"strong":[93],"potential":[94],"integration":[96],"into":[97],"Farm":[98],"Management":[99],"Information":[100],"Systems":[101],"data-driven":[103],"Model":[106],"interpretability":[107],"analysis":[108],"further":[109],"reveals":[110],"that,":[111],"with":[112],"adequate":[113],"training":[114],"data,":[115],"the":[116,123],"network":[117],"predominantly":[118],"relies":[119],"features":[121],"within":[122],"itself":[125],"inform":[127],"predictions,":[128],"suggesting":[129],"robustness":[130],"real-world":[132],"application":[133],"scenarios.":[134]},"counts_by_year":[],"updated_date":"2025-11-06T06:51:31.235846","created_date":"2025-10-10T00:00:00"}