{"id":"https://openalex.org/W7155058740","doi":"https://doi.org/10.48550/arxiv.2604.16743","title":"Automated Palynological Analysis System: Integrating Deep Metric Learning and $U^{2}$-Net Detection in $H\\infty$ bright field microscopy","display_name":"Automated Palynological Analysis System: Integrating Deep Metric Learning and $U^{2}$-Net Detection in $H\\infty$ bright field microscopy","publication_year":2026,"publication_date":"2026-04-17","ids":{"openalex":"https://openalex.org/W7155058740","doi":"https://doi.org/10.48550/arxiv.2604.16743"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.16743","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.16743","pdf_url":null,"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.16743","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134104579","display_name":"J. Staforelli-Vivanco","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Staforelli-Vivanco, J.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134205695","display_name":"R. Jofr\u00e9","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jofr\u00e9, R.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134167296","display_name":"B. Mu\u00f1oz","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mu\u00f1oz, B.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134162588","display_name":"V. Salamanca","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Salamanca, V.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134178876","display_name":"P. Coelho","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Coelho, P.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066714145","display_name":"I. Sanhueza","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sanhueza, I.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134103448","display_name":"L. Viafora","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Viafora, L.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134176957","display_name":"C. Toro","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Toro, C.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134128449","display_name":"J. Troncoso","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Troncoso, J.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123505867","display_name":"M. Rondanelli-Reyes","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rondanelli-Reyes, M.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134174174","display_name":"I. Lamas","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lamas, I.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10877","display_name":"Allergic Rhinitis and Sensitization","score":0.3264999985694885,"subfield":{"id":"https://openalex.org/subfields/2723","display_name":"Immunology and Allergy"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10877","display_name":"Allergic Rhinitis and Sensitization","score":0.3264999985694885,"subfield":{"id":"https://openalex.org/subfields/2723","display_name":"Immunology and Allergy"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10487","display_name":"Plant and animal studies","score":0.06109999865293503,"subfield":{"id":"https://openalex.org/subfields/1105","display_name":"Ecology, Evolution, Behavior and Systematics"},"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/T10702","display_name":"Insect and Arachnid Ecology and Behavior","score":0.04569999873638153,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.5479000210762024},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5108000040054321},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5030999779701233},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4578000009059906},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4284999966621399},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.42660000920295715},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.42080000042915344},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.39410001039505005}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7727000117301941},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6000000238418579},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.5479000210762024},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5170000195503235},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5108000040054321},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5030999779701233},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4578000009059906},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4284999966621399},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.42660000920295715},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.42080000042915344},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.39410001039505005},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.3596000075340271},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.3467999994754791},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.3181000053882599},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.30469998717308044},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.2937000095844269},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.28450000286102295},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.28439998626708984},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.2824000120162964},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.272599995136261},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.2703000009059906},{"id":"https://openalex.org/C147080431","wikidata":"https://www.wikidata.org/wiki/Q1074953","display_name":"Microscopy","level":2,"score":0.26420000195503235},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.25519999861717224}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.16743","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.16743","pdf_url":null,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.16743","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.16743","pdf_url":null,"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Traditional":[0],"melissopalynology":[1],"is":[2],"a":[3,62,90,95],"time-consuming":[4],"and":[5,37,61,83,94],"subjective":[6],"process,":[7],"often":[8],"taking":[9],"4-6":[10],"hours":[11],"per":[12],"sample.":[13],"We":[14],"present":[15],"an":[16],"automated,":[17],"high-throughput":[18],"microscopy":[19],"system":[20,54,88],"that":[21],"integrates":[22],"$H\\infty$":[23],"robust":[24],"mechanical":[25],"control":[26],"with":[27],"advanced":[28],"deep":[29],"learning":[30],"pipelines":[31],"for":[32,57,72],"the":[33,78],"precise":[34],"counting,":[35],"classification,":[36],"morphological":[38],"analysis":[39],"of":[40],"pollen":[41],"grains":[42],"from":[43],"Bio":[44,45],"region":[46],"in":[47,51],"south":[48],"central":[49],"territory":[50],"Chile.":[52],"Our":[53],"employs":[55],"$U^{2}$-Net":[56],"salient":[58],"object":[59],"detection":[60],"DINOv2":[63],"Vision":[64],"Transformer":[65],"backbone":[66],"trained":[67],"via":[68],"Deep":[69],"Metric":[70],"Learning":[71],"classification.":[73],"By":[74],"integrating":[75],"Gradient-Weighted":[76],"Attention,":[77],"model":[79],"provides":[80],"human-interpretable":[81],"texture":[82],"diagnostic":[84],"feature":[85],"annotations.":[86],"The":[87],"achieves":[89],"95.8$\\%$":[91],"classification":[92],"recall":[93],"6x":[96],"processing":[97],"speedup":[98],"compared":[99],"to":[100],"manual":[101],"expert":[102],"analysis.":[103]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-22T00:00:00"}
