{"id":"https://openalex.org/W3134010067","doi":"https://doi.org/10.1109/dicta51227.2020.9363407","title":"Fruit Detection in the Wild: The Impact of Varying Conditions and Cultivar","display_name":"Fruit Detection in the Wild: The Impact of Varying Conditions and Cultivar","publication_year":2020,"publication_date":"2020-11-29","ids":{"openalex":"https://openalex.org/W3134010067","doi":"https://doi.org/10.1109/dicta51227.2020.9363407","mag":"3134010067"},"language":"en","primary_location":{"id":"doi:10.1109/dicta51227.2020.9363407","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dicta51227.2020.9363407","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 Digital Image Computing: Techniques and Applications (DICTA)","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/A5046879011","display_name":"Michael Halstead","orcid":"https://orcid.org/0000-0001-7185-9304"},"institutions":[{"id":"https://openalex.org/I135140700","display_name":"University of Bonn","ror":"https://ror.org/041nas322","country_code":"DE","type":"education","lineage":["https://openalex.org/I135140700"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Michael Halstead","raw_affiliation_strings":["University of Bonn, Bonn, Germany"],"affiliations":[{"raw_affiliation_string":"University of Bonn, Bonn, Germany","institution_ids":["https://openalex.org/I135140700"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083626840","display_name":"Simon Denman","orcid":"https://orcid.org/0000-0002-0983-5480"},"institutions":[{"id":"https://openalex.org/I160993911","display_name":"Queensland University of Technology","ror":"https://ror.org/03pnv4752","country_code":"AU","type":"education","lineage":["https://openalex.org/I160993911"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Simon Denman","raw_affiliation_strings":["Queensland University of Technology, Brisbane, Australia"],"affiliations":[{"raw_affiliation_string":"Queensland University of Technology, Brisbane, Australia","institution_ids":["https://openalex.org/I160993911"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034095159","display_name":"Clinton Fookes","orcid":"https://orcid.org/0000-0002-8515-6324"},"institutions":[{"id":"https://openalex.org/I160993911","display_name":"Queensland University of Technology","ror":"https://ror.org/03pnv4752","country_code":"AU","type":"education","lineage":["https://openalex.org/I160993911"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Clinton Fookes","raw_affiliation_strings":["Queensland University of Technology, Brisbane, Australia"],"affiliations":[{"raw_affiliation_string":"Queensland University of Technology, Brisbane, Australia","institution_ids":["https://openalex.org/I160993911"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007627004","display_name":"Chris McCool","orcid":"https://orcid.org/0000-0002-0577-1299"},"institutions":[{"id":"https://openalex.org/I135140700","display_name":"University of Bonn","ror":"https://ror.org/041nas322","country_code":"DE","type":"education","lineage":["https://openalex.org/I135140700"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Chris McCool","raw_affiliation_strings":["University of Bonn, Bonn, Germany"],"affiliations":[{"raw_affiliation_string":"University of Bonn, Bonn, Germany","institution_ids":["https://openalex.org/I135140700"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5046879011"],"corresponding_institution_ids":["https://openalex.org/I135140700"],"apc_list":null,"apc_paid":null,"fwci":3.908,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.93094061,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9466999769210815,"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/T12894","display_name":"Date Palm Research Studies","score":0.9332000017166138,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7560590505599976},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6530750393867493},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6448100209236145},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.6332995295524597},{"id":"https://openalex.org/keywords/ripeness","display_name":"Ripeness","score":0.5286734104156494},{"id":"https://openalex.org/keywords/robotics","display_name":"Robotics","score":0.5173754096031189},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.49918580055236816},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4599570035934448},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4512932300567627},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4437529444694519},{"id":"https://openalex.org/keywords/cropping","display_name":"Cropping","score":0.4253529906272888},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4244050085544586},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.370887815952301},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.2968596816062927},{"id":"https://openalex.org/keywords/agriculture","display_name":"Agriculture","score":0.28003379702568054},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.132219135761261},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11755815148353577},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08923125267028809},{"id":"https://openalex.org/keywords/horticulture","display_name":"Horticulture","score":0.08916577696800232}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7560590505599976},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6530750393867493},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6448100209236145},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.6332995295524597},{"id":"https://openalex.org/C2780393073","wikidata":"https://www.wikidata.org/wiki/Q7335586","display_name":"Ripeness","level":3,"score":0.5286734104156494},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.5173754096031189},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.49918580055236816},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4599570035934448},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4512932300567627},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4437529444694519},{"id":"https://openalex.org/C13558536","wikidata":"https://www.wikidata.org/wiki/Q785116","display_name":"Cropping","level":3,"score":0.4253529906272888},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4244050085544586},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.370887815952301},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.2968596816062927},{"id":"https://openalex.org/C118518473","wikidata":"https://www.wikidata.org/wiki/Q11451","display_name":"Agriculture","level":2,"score":0.28003379702568054},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.132219135761261},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11755815148353577},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08923125267028809},{"id":"https://openalex.org/C144027150","wikidata":"https://www.wikidata.org/wiki/Q48803","display_name":"Horticulture","level":1,"score":0.08916577696800232},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C172353545","wikidata":"https://www.wikidata.org/wiki/Q2121926","display_name":"Ripening","level":2,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","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},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dicta51227.2020.9363407","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dicta51227.2020.9363407","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 Digital Image Computing: Techniques and Applications (DICTA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6200000047683716,"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger"}],"awards":[{"id":"https://openalex.org/G1693277229","display_name":null,"funder_award_id":"EXC 2070-390732324","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2094025749","https://openalex.org/W2108598243","https://openalex.org/W2109934232","https://openalex.org/W2223559401","https://openalex.org/W2409375369","https://openalex.org/W2501369945","https://openalex.org/W2573063466","https://openalex.org/W2613718673","https://openalex.org/W2737162192","https://openalex.org/W2796347433","https://openalex.org/W2809489825","https://openalex.org/W2909494862","https://openalex.org/W2945386048","https://openalex.org/W2963150697","https://openalex.org/W2967789058","https://openalex.org/W2974020870","https://openalex.org/W3004299129","https://openalex.org/W3099828420","https://openalex.org/W4293584584","https://openalex.org/W6620707391","https://openalex.org/W6673833707","https://openalex.org/W6750227808","https://openalex.org/W6762567233"],"related_works":["https://openalex.org/W2395543297","https://openalex.org/W2163911526","https://openalex.org/W2320112513","https://openalex.org/W2012057384","https://openalex.org/W2189509717","https://openalex.org/W3162834845","https://openalex.org/W2729298216","https://openalex.org/W4210897843","https://openalex.org/W2522789803","https://openalex.org/W2937446702"],"abstract_inverted_index":{"Agricultural":[0],"robotics":[1],"is":[2,23,65,154,237],"a":[3,25,44,60,103,201,225,246],"rapidly":[4],"evolving":[5],"research":[6],"field":[7],"due":[8,34,129],"to":[9,35,111,130,139,156,165,170,189,217,275,287],"advances":[10],"in":[11,72,102,119,133,224,255],"computer":[12],"vision,":[13],"machine":[14],"learning,":[15],"robotics,":[16],"and":[17,31,71,94,105,117,193,196,266,290],"increased":[18],"agricultural":[19],"demand.":[20],"However,":[21],"there":[22],"still":[24],"considerable":[26],"gap":[27],"between":[28,39],"farming":[29],"requirements":[30,173],"available":[32],"technology":[33],"the":[36,54,120,131,145,158,168,172,181,186,209,242,256,260,270,282],"large":[37],"differences":[38],"cropping":[40],"environments.":[41],"This":[42,150],"creates":[43],"pressing":[45],"need":[46],"for":[47,127,272],"models":[48],"with":[49,89],"greater":[50,253],"generalisability.":[51],"We":[52,97,183],"explore":[53],"issue":[55],"of":[56,174,180,211,222,248,262,284],"generalisability":[57,278],"by":[58,143,199,244],"considering":[59,208],"fruit":[61,195],"(sweet":[62],"pepper)":[63],"that":[64,234],"grown":[66],"using":[67,245],"different":[68,73,90],"cultivar":[69],"(sub-species)":[70],"environments":[74],"(field":[75],"vs":[76],"glasshouse).":[77],"To":[78],"investigate":[79],"these":[80,99,263],"differences,":[81],"we":[82,124,214,232],"publicly":[83],"release":[84],"three":[85,264],"novel":[86,265],"datasets":[87,101,249,268],"captured":[88],"domains,":[91],"cultivar,":[92],"cameras,":[93],"geographic":[95],"locations.":[96],"exploit":[98,185],"new":[100,175],"singular":[104],"combined":[106],"(to":[107],"promote":[108],"generalisation)":[109],"manner":[110],"evaluate":[112,291],"sweet":[113],"pepper":[114],"(fruit)":[115],"detection":[116,128,161],"classification":[118,203,207],"wild.":[121],"For":[122,205],"evaluation,":[123],"employ":[125],"Faster-RCNN":[126,187],"ease":[132],"which":[134],"it":[135],"can":[136],"be":[137],"expanded":[138],"incorporate":[140],"multitask":[141],"learning":[142,152,274],"utilising":[144],"Mask-RCNN":[146],"framework":[147],"(instance-based":[148],"segmentation).":[149],"multi-task":[151,273],"technique":[153],"shown":[155],"increase":[157],"cross":[159,226],"dataset":[160],"F1-Score":[162],"from":[163],"0.323":[164],"0.700,":[166],"demonstrating":[167],"potential":[169,271],"reduce":[171],"annotations":[176],"through":[177,252],"improved":[178],"generalisation":[179],"model.":[182],"further":[184],"architecture":[188],"include":[190],"both":[191],"super-":[192],"sub-classes,":[194],"ripeness":[197],"respectively,":[198],"incorporating":[200],"parallel":[202],"layer.":[204],"sub-class":[206],"percentage":[210],"correct":[212],"detections,":[213],"are":[215],"able":[216],"achieve":[218],"an":[219],"accuracy":[220],"score":[221],"0.900":[223],"domain":[227],"evaluation.":[228],"In":[229],"our":[230],"experiments,":[231],"find":[233],"intra-environmental":[235],"inference":[236],"generally":[238],"inferior,":[239],"however,":[240],"diversifying":[241],"data":[243,286],"combination":[247],"increases":[250],"performance":[251],"diversity":[254],"training":[257],"data.":[258],"Overall,":[259],"introduction":[261],"diverse":[267,285],"demonstrates":[269],"improve":[276],"cross-dataset":[277],"while":[279],"also":[280],"highlighting":[281],"importance":[283],"adequately":[288],"train":[289],"real-world":[292],"systems.":[293]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}