{"id":"https://openalex.org/W2981708487","doi":"https://doi.org/10.3390/s19204599","title":"Fruit Detection and Segmentation for Apple Harvesting Using Visual Sensor in Orchards","display_name":"Fruit Detection and Segmentation for Apple Harvesting Using Visual Sensor in Orchards","publication_year":2019,"publication_date":"2019-10-22","ids":{"openalex":"https://openalex.org/W2981708487","doi":"https://doi.org/10.3390/s19204599","mag":"2981708487","pmid":"https://pubmed.ncbi.nlm.nih.gov/31652634"},"language":"en","primary_location":{"id":"doi:10.3390/s19204599","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s19204599","pdf_url":"https://www.mdpi.com/1424-8220/19/20/4599/pdf?version=1571813850","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/19/20/4599/pdf?version=1571813850","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5038896099","display_name":"Hanwen Kang","orcid":"https://orcid.org/0000-0001-5553-9239"},"institutions":[{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Hanwen Kang","raw_affiliation_strings":["Laboratory of Motion Generation and Analysis, Faculty of Engineering, Monash University, Clayton, VIC 3800, Australia"],"affiliations":[{"raw_affiliation_string":"Laboratory of Motion Generation and Analysis, Faculty of Engineering, Monash University, Clayton, VIC 3800, Australia","institution_ids":["https://openalex.org/I56590836"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100763733","display_name":"Chao Chen","orcid":"https://orcid.org/0000-0002-1443-8017"},"institutions":[{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Chao Chen","raw_affiliation_strings":["Laboratory of Motion Generation and Analysis, Faculty of Engineering, Monash University, Clayton, VIC 3800, Australia"],"affiliations":[{"raw_affiliation_string":"Laboratory of Motion Generation and Analysis, Faculty of Engineering, Monash University, Clayton, VIC 3800, Australia","institution_ids":["https://openalex.org/I56590836"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100763733"],"corresponding_institution_ids":["https://openalex.org/I56590836"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":19.7893,"has_fulltext":true,"cited_by_count":133,"citation_normalized_percentile":{"value":0.99356601,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"19","issue":"20","first_page":"4599","last_page":"4599"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9995999932289124,"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":0.9995999932289124,"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/T12894","display_name":"Date Palm Research Studies","score":0.9769999980926514,"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/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.955299973487854,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/segmentation","display_name":"Segmentation","score":0.8457919359207153},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6999378800392151},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.670923113822937},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.5677688121795654},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.5659988522529602},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5423274040222168},{"id":"https://openalex.org/keywords/network-architecture","display_name":"Network architecture","score":0.4816645383834839},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.47270700335502625},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4624170958995819},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.45950621366500854},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.43610602617263794},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.41115960478782654},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11963734030723572},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.06290304660797119}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.8457919359207153},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6999378800392151},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.670923113822937},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.5677688121795654},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.5659988522529602},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5423274040222168},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.4816645383834839},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.47270700335502625},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4624170958995819},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.45950621366500854},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.43610602617263794},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.41115960478782654},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11963734030723572},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.06290304660797119},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":7,"locations":[{"id":"doi:10.3390/s19204599","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s19204599","pdf_url":"https://www.mdpi.com/1424-8220/19/20/4599/pdf?version=1571813850","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:31652634","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/31652634","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:arXiv.org:2003.13298","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2003.13298","pdf_url":"https://arxiv.org/pdf/2003.13298","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:monash.edu:openaire/31d740b3-7f7a-405d-8dda-df2a63fde13e","is_oa":true,"landing_page_url":"https://research.monash.edu/en/publications/31d740b3-7f7a-405d-8dda-df2a63fde13e","pdf_url":"https://researchmgt.monash.edu/ws/files/286990314/286990220_oa.pdf","source":{"id":"https://openalex.org/S4306402625","display_name":"Monash University Research Portal (Monash University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I56590836","host_organization_name":"Monash University","host_organization_lineage":["https://openalex.org/I56590836"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Kang, H & Chen, C 2019, 'Fruit detection and segmentation for apple harvesting using visual sensor in orchards', Sensors, vol. 19, no. 20, 4599. https://doi.org/10.3390/s19204599","raw_type":"article"},{"id":"pmh:oai:doaj.org/article:8e095ccfc2c843d6aeaacab85d227bec","is_oa":true,"landing_page_url":"https://doaj.org/article/8e095ccfc2c843d6aeaacab85d227bec","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 19, Iss 20, p 4599 (2019)","raw_type":"article"},{"id":"pmh:oai:europepmc.org:5826636","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6832306","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"},{"id":"pmh:oai:mdpi.com:/1424-8220/19/20/4599/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/s19204599","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s19204599","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s19204599","pdf_url":"https://www.mdpi.com/1424-8220/19/20/4599/pdf?version=1571813850","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6600000262260437,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2981708487.pdf","grobid_xml":"https://content.openalex.org/works/W2981708487.grobid-xml"},"referenced_works_count":69,"referenced_works":["https://openalex.org/W46659105","https://openalex.org/W1483870316","https://openalex.org/W1536680647","https://openalex.org/W1849277567","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1980180165","https://openalex.org/W2018563411","https://openalex.org/W2031489346","https://openalex.org/W2064675550","https://openalex.org/W2087016914","https://openalex.org/W2088049833","https://openalex.org/W2098976163","https://openalex.org/W2102605133","https://openalex.org/W2105568170","https://openalex.org/W2145072179","https://openalex.org/W2157331557","https://openalex.org/W2163808566","https://openalex.org/W2193145675","https://openalex.org/W2194775991","https://openalex.org/W2274287116","https://openalex.org/W2409375369","https://openalex.org/W2412782625","https://openalex.org/W2432481613","https://openalex.org/W2467954037","https://openalex.org/W2501369945","https://openalex.org/W2506469762","https://openalex.org/W2543665758","https://openalex.org/W2560023338","https://openalex.org/W2564790728","https://openalex.org/W2565516711","https://openalex.org/W2570343428","https://openalex.org/W2579985080","https://openalex.org/W2593868148","https://openalex.org/W2599765304","https://openalex.org/W2609077090","https://openalex.org/W2613718673","https://openalex.org/W2630837129","https://openalex.org/W2765889543","https://openalex.org/W2767547957","https://openalex.org/W2770233088","https://openalex.org/W2790979755","https://openalex.org/W2795783309","https://openalex.org/W2796347433","https://openalex.org/W2802474463","https://openalex.org/W2804860796","https://openalex.org/W2898718544","https://openalex.org/W2909494862","https://openalex.org/W2909501706","https://openalex.org/W2920621226","https://openalex.org/W2940183409","https://openalex.org/W2950635152","https://openalex.org/W2951548327","https://openalex.org/W2953106684","https://openalex.org/W2953151638","https://openalex.org/W2962914239","https://openalex.org/W2963150697","https://openalex.org/W2963523428","https://openalex.org/W2963881378","https://openalex.org/W2964309882","https://openalex.org/W2964350391","https://openalex.org/W2967007053","https://openalex.org/W3012291630","https://openalex.org/W3106250896","https://openalex.org/W3121285516","https://openalex.org/W4250482878","https://openalex.org/W6602002561","https://openalex.org/W6681554747","https://openalex.org/W6687483927"],"related_works":["https://openalex.org/W2953234277","https://openalex.org/W2626256601","https://openalex.org/W2022849497","https://openalex.org/W3081299480","https://openalex.org/W2407190427","https://openalex.org/W2907584218","https://openalex.org/W2919210741","https://openalex.org/W3002446410","https://openalex.org/W4390224712","https://openalex.org/W4322096758"],"abstract_inverted_index":{"Autonomous":[0],"harvesting":[1,26],"shows":[2],"a":[3,31,86],"promising":[4],"prospect":[5],"in":[6,24,45,147,211],"the":[7,14,20,49,59,64,78,83,91,98,100,121,129,143,148,157,166,179,196,203],"future":[8],"development":[9],"of":[10,19,41,74,82,118,123,132,154,159,168,178,208],"theagriculture":[11],"industry,":[12],"while":[13],"vision":[15],"system":[16],"is":[17,95],"one":[18],"most":[21],"challenging":[22],"components":[23],"theautonomous":[25],"technologies.":[27],"This":[28],"work":[29],"proposes":[30],"multi-function":[32],"network":[33,57,68,84,88,93,104,138,180,199],"to":[34,69],"perform":[35,202],"thereal-time":[36],"detection":[37,54,101,122,158,197,205],"and":[38,43,55,63,102,111,125,134,161,163,175,187,206],"semantic":[39,130],"segmentation":[40,56,103,112,131,167,207],"apples":[42,124,133,160,169],"branches":[44,210],"orchard":[46],"environments":[47],"byusing":[48],"visual":[50],"sensor.":[51],"The":[52,137,172,191],"developed":[53],"utilises":[58],"atrous":[60],"spatialpyramid":[61],"pooling":[62],"gate":[65],"feature":[66,71],"pyramid":[67],"enhance":[70],"extraction":[72],"ability":[73],"thenetwork.":[75],"To":[76],"improve":[77],"real-time":[79,204],"computation":[80,145,176],"performance":[81],"model,":[85],"lightweightbackbone":[87,183],"based":[89],"on":[90,109,120,128,156,165],"residual":[92],"architecture":[94],"developed.":[96],"From":[97],"experimentalresults,":[99],"with":[105,182],"ResNet-101":[106],"backbone":[107,141],"outperformed":[108],"thedetection":[110],"tasks,":[113],"achieving":[114],"an":[115,152],"<i>F</i>1":[116],"score":[117],"0.832":[119],"87.6%and":[126],"77.2%":[127],"branches,":[135],"respectively.":[136,171,190],"modelwith":[139],"lightweight":[140],"showed":[142],"best":[144],"efficiency":[146],"results.":[149],"It":[150],"achieved":[151],"<i>F</i>1score":[153],"0.827":[155],"86.5%":[162],"75.7%":[164],"andbranches,":[170],"weights":[173],"size":[174],"time":[177],"model":[181],"were":[184],"12.8":[185],"M":[186],"32":[188],"ms,":[189],"experimental":[192],"results":[193],"show":[194],"that":[195],"andsegmentation":[198],"can":[200],"effectively":[201],"applesand":[209],"orchards.":[212]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":25},{"year":2023,"cited_by_count":24},{"year":2022,"cited_by_count":23},{"year":2021,"cited_by_count":27},{"year":2020,"cited_by_count":17},{"year":2019,"cited_by_count":1}],"updated_date":"2026-04-07T14:57:38.498316","created_date":"2025-10-10T00:00:00"}