{"id":"https://openalex.org/W7138897553","doi":"https://doi.org/10.5220/0014063900004084","title":"HyperNut: Hyper Spectral Dataset of Nuts for Unsupervised Defect Detection and Segmentation","display_name":"HyperNut: Hyper Spectral Dataset of Nuts for Unsupervised Defect Detection and Segmentation","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7138897553","doi":"https://doi.org/10.5220/0014063900004084"},"language":"en","primary_location":{"id":"doi:10.5220/0014063900004084","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0014063900004084","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 21st International Conference on Computer Vision Theory and Applications","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.5220/0014063900004084","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5069887601","display_name":"Afshin Dini","orcid":"https://orcid.org/0000-0001-6234-3322"},"institutions":[{"id":"https://openalex.org/I166825849","display_name":"Tampere University","ror":"https://ror.org/033003e23","country_code":"FI","type":"education","lineage":["https://openalex.org/I166825849"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Afshin Dini","raw_affiliation_strings":["Unit of Computing Sciences, Tampere University, Finland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Unit of Computing Sciences, Tampere University, Finland","institution_ids":["https://openalex.org/I166825849"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129879494","display_name":"Farnaz Delirie","orcid":null},"institutions":[{"id":"https://openalex.org/I166825849","display_name":"Tampere University","ror":"https://ror.org/033003e23","country_code":"FI","type":"education","lineage":["https://openalex.org/I166825849"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Farnaz Delirie","raw_affiliation_strings":["Unit of Computing Sciences, Tampere University, Finland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Unit of Computing Sciences, Tampere University, Finland","institution_ids":["https://openalex.org/I166825849"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088180438","display_name":"Esa Rahtu","orcid":"https://orcid.org/0000-0001-8767-0864"},"institutions":[{"id":"https://openalex.org/I166825849","display_name":"Tampere University","ror":"https://ror.org/033003e23","country_code":"FI","type":"education","lineage":["https://openalex.org/I166825849"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Esa Rahtu","raw_affiliation_strings":["Unit of Computing Sciences, Tampere University, Finland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Unit of Computing Sciences, Tampere University, Finland","institution_ids":["https://openalex.org/I166825849"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I166825849"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.28798962,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"177","last_page":"184"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.4982999861240387,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.4982999861240387,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.2409999966621399,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.04729999974370003,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5843999981880188},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5799000263214111},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.31470000743865967},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.30390000343322754},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.2928999960422516}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6773999929428101},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5843999981880188},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5799000263214111},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5598000288009644},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.31470000743865967},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3070000112056732},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.30390000343322754},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2928999960422516},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2524999976158142},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.23909999430179596}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.5220/0014063900004084","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0014063900004084","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 21st International Conference on Computer Vision Theory and Applications","raw_type":"proceedings-article"},{"id":"pmh:oai:trepo.tuni.fi:10024/236689","is_oa":true,"landing_page_url":"https://trepo.tuni.fi/handle/10024/236689","pdf_url":null,"source":{"id":"https://openalex.org/S4306401860","display_name":"Tampere University Institutional Repository (Tampere University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I150589677","host_organization_name":"Tampere University of Applied Sciences","host_organization_lineage":["https://openalex.org/I150589677"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference"}],"best_oa_location":{"id":"doi:10.5220/0014063900004084","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0014063900004084","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 21st International Conference on Computer Vision Theory and Applications","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/2","score":0.7822139859199524,"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":{"Hyperspectral":[0],"Imaging":[1],"(HSI),":[2],"providing":[3,93,121],"detailed":[4],"information":[5],"from":[6],"various":[7],"spectrums,":[8],"is":[9,20,76],"a":[10,21,86],"suitable":[11,159],"candidate":[12],"for":[13,60,67,161],"detecting":[14],"defects":[15,127],"in":[16,24,43,80,128],"real-world":[17,101],"applications,":[18],"which":[19],"hot":[22],"topic":[23],"the":[25,33,44,77,81,141,145,151],"field":[26],"of":[27,39,89,96,126],"computer":[28],"vision":[29],"nowadays.":[30],"We":[31],"introduce":[32],"HyperNut":[34],"dataset,":[35],"containing":[36,103],"hyperspectral":[37,142,156],"images":[38,148,157],"almonds":[40],"and":[41,46,64,106,109,115,135,144,149],"pistachios":[42],"visible":[45],"near-infrared":[47],"(VIS-NIR)":[48],"ranges":[49],"(400nm-1000nm).":[50],"This":[51],"dataset":[52,75],"contains":[53],"non-anomalous":[54],"samples":[55,66,102],"that":[56,83,155],"can":[57],"be":[58],"used":[59],"training":[61],"unsupervised":[62],"approaches":[63],"defective":[65,97],"testing":[68],"purposes.":[69],"To":[70],"our":[71,74],"best":[72],"knowledge,":[73],"only":[78],"one":[79],"literature":[82],"(a)":[84],"allows":[85,117],"thorough":[87],"analysis":[88],"nuts":[90],"quality":[91],"by":[92,120],"different":[94],"types":[95],"samples,":[98],"(b)":[99],"provides":[100],"multiple":[104],"objects":[105],"considering":[107],"noise":[108],"variable":[110],"environmental":[111],"conditions":[112],"while":[113],"sampling,":[114],"(c)":[116],"defect":[118,162],"segmentation":[119],"masks":[122],"presenting":[123],"exact":[124],"locations":[125],"samples.":[129],"Moreover,":[130],"we":[131],"have":[132],"tested":[133],"basic":[134],"simple":[136],"anomaly":[137],"detection":[138,163],"methods":[139],"on":[140],"data":[143],"related":[146],"RGB":[147],"compared":[150],"results":[152],"to":[153],"show":[154],"are":[158],"candidates":[160],"problems.":[164]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-03-20T00:00:00"}
