{"id":"https://openalex.org/W2799213538","doi":"https://doi.org/10.1109/icfhr-2018.2018.00080","title":"DeepDIVA: A Highly-Functional Python Framework for Reproducible Experiments","display_name":"DeepDIVA: A Highly-Functional Python Framework for Reproducible Experiments","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2799213538","doi":"https://doi.org/10.1109/icfhr-2018.2018.00080","mag":"2799213538"},"language":"en","primary_location":{"id":"doi:10.1109/icfhr-2018.2018.00080","doi":"https://doi.org/10.1109/icfhr-2018.2018.00080","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icfhr-2018.2018.00080","pdf_url":null,"source":{"id":"https://openalex.org/S4306419466","display_name":"International Conference on Frontiers in Handwriting Recognition","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 16th International Conference on Frontiers in Handwriting Recognition (ICFHR)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1805.00329","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087037717","display_name":"Michele Alberti","orcid":"https://orcid.org/0009-0001-4352-4555","observed_orcids":["https://orcid.org/0009-0001-4352-4555"]},"institutions":[{"id":"https://openalex.org/I154338468","display_name":"University of Fribourg","ror":"https://ror.org/022fs9h90","country_code":"CH","type":"education","lineage":["https://openalex.org/I154338468"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Michele Alberti","raw_affiliation_strings":["Document Image and Voice Analysis Group (DIVA) University of Fribourg, Switzerland","University of Fribourg, Fribourg, Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Document Image and Voice Analysis Group (DIVA) University of Fribourg, Switzerland","institution_ids":["https://openalex.org/I154338468"]},{"raw_affiliation_string":"University of Fribourg, Fribourg, Switzerland","institution_ids":["https://openalex.org/I154338468"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070046964","display_name":"Vinaychandran Pondenkandath","orcid":"https://orcid.org/0000-0001-5883-0849","observed_orcids":["https://orcid.org/0000-0001-5883-0849"]},"institutions":[{"id":"https://openalex.org/I154338468","display_name":"University of Fribourg","ror":"https://ror.org/022fs9h90","country_code":"CH","type":"education","lineage":["https://openalex.org/I154338468"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Vinaychandran Pondenkandath","raw_affiliation_strings":["Document Image and Voice Analysis Group (DIVA) University of Fribourg, Switzerland","University of Fribourg, Fribourg, Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Document Image and Voice Analysis Group (DIVA) University of Fribourg, Switzerland","institution_ids":["https://openalex.org/I154338468"]},{"raw_affiliation_string":"University of Fribourg, Fribourg, Switzerland","institution_ids":["https://openalex.org/I154338468"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041551003","display_name":"Marcel W\u00fcrsch","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I154338468","display_name":"University of Fribourg","ror":"https://ror.org/022fs9h90","country_code":"CH","type":"education","lineage":["https://openalex.org/I154338468"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Marcel Wursch","raw_affiliation_strings":["Document Image and Voice Analysis Group (DIVA) University of Fribourg, Switzerland","University of Fribourg, Fribourg, Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Document Image and Voice Analysis Group (DIVA) University of Fribourg, Switzerland","institution_ids":["https://openalex.org/I154338468"]},{"raw_affiliation_string":"University of Fribourg, Fribourg, Switzerland","institution_ids":["https://openalex.org/I154338468"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018014670","display_name":"Rolf Ingold","orcid":"https://orcid.org/0000-0001-7738-133X","observed_orcids":["https://orcid.org/0000-0001-7738-133X"]},"institutions":[{"id":"https://openalex.org/I154338468","display_name":"University of Fribourg","ror":"https://ror.org/022fs9h90","country_code":"CH","type":"education","lineage":["https://openalex.org/I154338468"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Rolf Ingold","raw_affiliation_strings":["Document Image and Voice Analysis Group (DIVA) University of Fribourg, Switzerland","University of Fribourg, Fribourg, Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Document Image and Voice Analysis Group (DIVA) University of Fribourg, Switzerland","institution_ids":["https://openalex.org/I154338468"]},{"raw_affiliation_string":"University of Fribourg, Fribourg, Switzerland","institution_ids":["https://openalex.org/I154338468"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073619925","display_name":"Marcus Liwicki","orcid":"https://orcid.org/0000-0003-4029-6574","observed_orcids":["https://orcid.org/0000-0003-4029-6574"]},"institutions":[{"id":"https://openalex.org/I154338468","display_name":"University of Fribourg","ror":"https://ror.org/022fs9h90","country_code":"CH","type":"education","lineage":["https://openalex.org/I154338468"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Marcus Liwicki","raw_affiliation_strings":["Document Image and Voice Analysis Group (DIVA) University of Fribourg, Switzerland","University of Fribourg, Fribourg, Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Document Image and Voice Analysis Group (DIVA) University of Fribourg, Switzerland","institution_ids":["https://openalex.org/I154338468"]},{"raw_affiliation_string":"University of Fribourg, Fribourg, Switzerland","institution_ids":["https://openalex.org/I154338468"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I154338468"],"apc_list":null,"apc_paid":null,"fwci":8.8338,"has_fulltext":true,"cited_by_count":34,"citation_normalized_percentile":{"value":0.9846343,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"423","last_page":"428"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11986","display_name":"Scientific Computing and Data Management","score":0.8407999873161316,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11986","display_name":"Scientific Computing and Data Management","score":0.8407999873161316,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.10830000042915344,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.02019999921321869,"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/experimental-reproducibility","display_name":"experimental reproducibility","score":0.8840000033378601},{"id":"https://openalex.org/keywords/document-image-analysis","display_name":"document image analysis","score":0.8519999980926514},{"id":"https://openalex.org/keywords/handwritten-document-analysis","display_name":"handwritten document analysis","score":0.9309999942779541},{"id":"https://openalex.org/keywords/hyperparameter-optimization","display_name":"hyperparameter optimization","score":0.6819999814033508},{"id":"https://openalex.org/keywords/experiment-tracking","display_name":"experiment tracking","score":0.7639999985694885},{"id":"https://openalex.org/keywords/python-framework","display_name":"Python framework","score":0.5630000233650208},{"id":"https://openalex.org/keywords/pytorch","display_name":"PyTorch","score":0.9649999737739563},{"id":"https://openalex.org/keywords/open-source-software","display_name":"open source software","score":0.7390000224113464},{"id":"https://openalex.org/keywords/web-services","display_name":"web services","score":0.5860000252723694},{"id":"https://openalex.org/keywords/research-infrastructure","display_name":"research infrastructure","score":0.32499998807907104}],"concepts":[{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.8944417834281921},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8335397243499756},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.6224817037582397},{"id":"https://openalex.org/C75701414","wikidata":"https://www.wikidata.org/wiki/Q1651672","display_name":"Boilerplate text","level":2,"score":0.49735763669013977},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.4863582253456116},{"id":"https://openalex.org/C3018397939","wikidata":"https://www.wikidata.org/wiki/Q3644502","display_name":"Open source","level":3,"score":0.45024845004081726},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3894907534122467},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.36859434843063354},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35966500639915466},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.3496166467666626},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.3440408706665039},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32470887899398804},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3223622143268585},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.22644385695457458}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1109/icfhr-2018.2018.00080","doi":"https://doi.org/10.1109/icfhr-2018.2018.00080","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icfhr-2018.2018.00080","pdf_url":null,"source":{"id":"https://openalex.org/S4306419466","display_name":"International Conference on Frontiers in Handwriting Recognition","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 16th International Conference on Frontiers in Handwriting Recognition (ICFHR)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1805.00329","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1805.00329","pdf_url":"https://arxiv.org/pdf/1805.00329","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"mag:2799213538","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1805.00329","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"arXiv (Cornell University)","raw_type":null},{"id":"pmh:oai:arbor.bfh.ch:20052","doi":null,"is_oa":false,"landing_page_url":"https://arbor.bfh.ch/20052/","pdf_url":null,"source":{"id":"https://openalex.org/S4406922806","display_name":"ARBOR - Bern University of Applied Sciences Repository","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Alberti, Michele; Pondenkandath, Vinaychandran; Gygli, Marcel; Ingold, Rolf; Liwicki, Marcus (8 August 2018). DeepDIVA: A Highly-Functional Python Framework for Reproducible Experiments In: 2018 16th International Conference on Frontiers in Handwriting Recognition (ICFHR) (pp. 423-428). New York: IEEE 10.1109/ICFHR-2018.2018.00080 &lt;http://dx.doi.org/10.1109/ICFHR-2018.2018.00080&gt;","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"doi:10.48550/arxiv.1805.00329","doi":"https://doi.org/10.48550/arxiv.1805.00329","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1805.00329","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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"},{"id":"doi:10.24451/arbor.20052","doi":"https://doi.org/10.24451/arbor.20052","is_oa":true,"landing_page_url":"https://doi.org/10.24451/arbor.20052","pdf_url":null,"source":{"id":"https://openalex.org/S7407051224","display_name":"BFH: ARBOR","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1805.00329","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1805.00329","pdf_url":"https://arxiv.org/pdf/1805.00329","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G8290233684","display_name":"HisDoc III : Large-Scale Historical Document Classification","funder_award_id":"169618","funder_id":"https://openalex.org/F4320320924","funder_display_name":"Schweizerischer Nationalfonds zur F\u00f6rderung der Wissenschaftlichen Forschung"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320320924","display_name":"Schweizerischer Nationalfonds zur F\u00f6rderung der Wissenschaftlichen Forschung","ror":"https://ror.org/00yjd3n13"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2799213538.pdf","grobid_xml":"https://content.openalex.org/works/W2799213538.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W1971700225","https://openalex.org/W1975517671","https://openalex.org/W1980181946","https://openalex.org/W2079336662","https://openalex.org/W2100267603","https://openalex.org/W2132862423","https://openalex.org/W2156332201","https://openalex.org/W2194775991","https://openalex.org/W2292391400","https://openalex.org/W2431100065","https://openalex.org/W2754336679","https://openalex.org/W2765084367","https://openalex.org/W2787225861","https://openalex.org/W2787494303","https://openalex.org/W2787623536","https://openalex.org/W2795661667","https://openalex.org/W2810427255","https://openalex.org/W2907050536","https://openalex.org/W2952331513","https://openalex.org/W2962933129","https://openalex.org/W7028574699"],"related_works":["https://openalex.org/W2950452248","https://openalex.org/W7134829601","https://openalex.org/W4385470899","https://openalex.org/W2946131944","https://openalex.org/W7065212417","https://openalex.org/W7162506222","https://openalex.org/W4389524522","https://openalex.org/W3035495837","https://openalex.org/W3087897998","https://openalex.org/W2746769743"],"abstract_inverted_index":{"We":[0],"introduce":[1],"DeepDIVA:":[2],"an":[3],"infrastructure":[4],"designed":[5],"to":[6],"enable":[7],"quick":[8],"and":[9,79,83,116,128],"intuitive":[10],"setup":[11],"of":[12,19,67,75,81,89,100],"reproducible":[13],"experiments":[14,57],"with":[15,58],"a":[16,28,45,50,64],"large":[17,65],"range":[18,66],"useful":[20],"analysis":[21,36,103],"functionality.":[22,110],"Reproducing":[23],"scientific":[24],"results":[25],"can":[26,47],"be":[27],"frustrating":[29],"experience,":[30],"not":[31],"only":[32],"in":[33,38,41,97,114],"document":[34,102],"image":[35],"but":[37],"machine":[39],"learning":[40,120],"general.":[42],"Using":[43],"DeepDIVA":[44,111],"researcher":[46],"either":[48],"reproduce":[49],"given":[51],"experiment":[52],"or":[53],"share":[54],"their":[55],"own":[56],"others.":[59],"Moreover,":[60],"the":[61,87,98,108,118],"framework":[62,121],"offers":[63],"functions,":[68],"such":[69],"as":[70,130],"boilerplate":[71],"code,":[72],"keeping":[73],"track":[74],"experiments,":[76],"hyper-parameter":[77],"optimization,":[78],"visualization":[80],"data":[82],"results.":[84],"To":[85],"demonstrate":[86],"effectiveness":[88],"this":[90,92],"framework,":[91],"paper":[93],"presents":[94],"case":[95],"studies":[96],"area":[99],"handwritten":[101],"where":[104],"researchers":[105],"benefit":[106],"from":[107],"integrated":[109],"is":[112,124],"implemented":[113],"Python":[115],"uses":[117],"deep":[119],"PyTorch.":[122],"It":[123],"completely":[125],"open":[126],"source,":[127],"accessible":[129],"Web":[131],"Service":[132],"through":[133],"DIVAServices.":[134]},"counts_by_year":[{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":4}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2018-05-07T00:00:00"}
