Publicação
Obtaining deep learning models for automatic classification of leukocytes
| Resumo: | In this work, the authors classify leukocyte images using the neural network architectures that won the annual ILSVRC competition. The classification of leukocytes is made using pretrained networks and the same networks trained from scratch in order to select the ones that achieve the best performance for the intended task. The categories used are eosinophils, lymphocytes, monocytes, and neutrophils. The analysis of the results takes into account the amount of training required, the regularization techniques used, the training time, and the accuracy in image classification. The best classification results, on the order of 98%, suggest that it is possible, considering a competent preprocessing, to train a network like the DenseNet with 169 or 201 layers, in about 100 epochs, to classify leukocytes in microscopy images. |
|---|---|
| Autores principais: | Rodrigues, Pedro João |
| Outros Autores: | Igrejas, Getúlio; Beato, Romeu Ferreira |
| Assunto: | Deep learning Leukocytes |
| Ano: | 2020 |
| País: | Portugal |
| Tipo de documento: | capítulo de livro |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade Politécnica de Bragança |
| Idioma: | inglês |
| Origem: | Biblioteca Digital da UPB |
| _version_ | 1877782611426803712 |
|---|---|
| author | Rodrigues, Pedro João |
| author2 | Igrejas, Getúlio Beato, Romeu Ferreira |
| author2_role | author author |
| author_facet | Rodrigues, Pedro João Igrejas, Getúlio Beato, Romeu Ferreira |
| author_role | author |
| contributor_name_str_mv | Biblioteca Digital da UPB |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Rodrigues, Pedro João\",\"Person.identifier.cienciaID\":\"1316-21BB-9015\",\"Person.identifier.orcid\":\"0000-0002-0555-2029\"},{\"Person.name\":\"Igrejas, Getúlio\",\"Person.identifier.orcid\":\"0000-0002-6820-8858\",\"Person.identifier.researcherID\":\"M-8571-2013\",\"Person.identifier.scopusAuthorID\":\"47761255900\"},{\"Person.name\":\"Beato, Romeu Ferreira\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | Biblioteca Digital da UPB |
| datacite.creators.creator.creatorName.fl_str_mv | Rodrigues, Pedro João Igrejas, Getúlio Beato, Romeu Ferreira |
| datacite.date.Accepted.fl_str_mv | 2020-01-01T00:00:00Z |
| datacite.date.available.fl_str_mv | 2020-07-27T14:32:40Z |
| datacite.date.embargoed.fl_str_mv | 2020-07-27T14:32:40Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.fl_str_mv | Deep learning Leukocytes |
| datacite.titles.title.fl_str_mv | Obtaining deep learning models for automatic classification of leukocytes |
| dc.contributor.none.fl_str_mv | Biblioteca Digital da UPB |
| dc.creator.none.fl_str_mv | Rodrigues, Pedro João Igrejas, Getúlio Beato, Romeu Ferreira |
| dc.date.Accepted.fl_str_mv | 2020-01-01T00:00:00Z |
| dc.date.available.fl_str_mv | 2020-07-27T14:32:40Z |
| dc.date.embargoed.fl_str_mv | 2020-07-27T14:32:40Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://hdl.handle.net/10198/22527 |
| dc.language.none.fl_str_mv | eng |
| dc.publisher.none.fl_str_mv | IGI Global |
| dc.rights.cclincense.fl_str_mv | http://creativecommons.org/licenses/by/4.0/ |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.subject.none.fl_str_mv | Deep learning Leukocytes |
| dc.title.fl_str_mv | Obtaining deep learning models for automatic classification of leukocytes |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_3248 |
| description | In this work, the authors classify leukocyte images using the neural network architectures that won the annual ILSVRC competition. The classification of leukocytes is made using pretrained networks and the same networks trained from scratch in order to select the ones that achieve the best performance for the intended task. The categories used are eosinophils, lymphocytes, monocytes, and neutrophils. The analysis of the results takes into account the amount of training required, the regularization techniques used, the training time, and the accuracy in image classification. The best classification results, on the order of 98%, suggest that it is possible, considering a competent preprocessing, to train a network like the DenseNet with 169 or 201 layers, in about 100 epochs, to classify leukocytes in microscopy images. |
| dirty | 0 |
| eu_rights_str_mv | openAccess |
| format | bookPart |
| fulltext.url.fl_str_mv | https://bibliotecadigital.unipb.pt/bitstreams/16442f87-768a-45f2-a552-fb63200e4065/download |
| id | ipb_c2b35ef619f8a549f874bf2be605c4e4 |
| identifier.url.fl_str_mv | http://hdl.handle.net/10198/22527 |
| inst_facet_str | urn:organizationAcronym:unipb{{{_:::_}}}Universidade Politécnica de Bragança |
| instacron_str | unipb |
| institution | Universidade Politécnica de Bragança |
| instname_str | Universidade Politécnica de Bragança |
| language | eng |
| network_acronym_str | ipb |
| network_name_str | Biblioteca Digital da UPB |
| oai_identifier_str | oai:bibliotecadigital.unipb.pt:10198/22527 |
| organization_str_mv | urn:organizationAcronym:unipb |
| person_str_mv | Rodrigues, Pedro João Rodrigues, Pedro João https://www.ciencia-id.pt/1316-21BB-9015 1316-21BB-9015 http://orcid.org/0000-0002-0555-2029 0000-0002-0555-2029 Igrejas, Getúlio Igrejas, Getúlio http://orcid.org/0000-0002-6820-8858 0000-0002-6820-8858 Beato, Romeu Ferreira |
| publishDate | 2020 |
| publisher.none.fl_str_mv | IGI Global |
| repo_facet_str | urn:repositoryAcronym:ipb{{{_:::_}}}Biblioteca Digital da UPB |
| reponame_str | Biblioteca Digital da UPB |
| repository_id_str | urn:repositoryAcronym:ipb |
| service_str_mv | urn:repositoryAcronym:ipb |
| spelling | engIGI Globalpt_PTIn this work, the authors classify leukocyte images using the neural network architectures that won the annual ILSVRC competition. The classification of leukocytes is made using pretrained networks and the same networks trained from scratch in order to select the ones that achieve the best performance for the intended task. The categories used are eosinophils, lymphocytes, monocytes, and neutrophils. The analysis of the results takes into account the amount of training required, the regularization techniques used, the training time, and the accuracy in image classification. The best classification results, on the order of 98%, suggest that it is possible, considering a competent preprocessing, to train a network like the DenseNet with 169 or 201 layers, in about 100 epochs, to classify leukocytes in microscopy images.application/pdfpt_PTObtaining deep learning models for automatic classification of leukocytesPersonalRodrigues, Pedro JoãoDSpacehttp://dspace.org/items/6c5911a6-b62b-4876-9def-60096b52383aDSpacehttp://dspace.org/items/6c5911a6-b62b-4876-9def-60096b52383aRodriguesPedro JoãoCiência IDhttps://www.ciencia-id.pt1316-21BB-9015ORCIDhttp://orcid.org0000-0002-0555-2029PersonalIgrejas, GetúlioDSpacehttp://dspace.org/items/ab4092ec-d1b1-4fe0-b65a-efba1310fd5aDSpacehttp://dspace.org/items/ab4092ec-d1b1-4fe0-b65a-efba1310fd5aIgrejasGetúlioORCIDhttp://orcid.org0000-0002-6820-8858Researcher IDhttps://www.researcherid.comM-8571-2013Scopus Author IDhttps://www.scopus.com47761255900Beato, Romeu FerreiraHostingInstitutionOrganizationalBiblioteca Digital da UPBe-mailmailto:dspace@unipb.ptdspace@unipb.ptDOIIsPartOf10.4018/978-1-7998-3095-5.ch0012020-07-27T14:32:40Z20202020-01-01T00:00:00ZHandlehttp://hdl.handle.net/10198/22527http://purl.org/coar/access_right/c_abf2open accessDeep learningLeukocytes2345365 bytesliteraturehttp://purl.org/coar/resource_type/c_3248book part2020http://creativecommons.org/licenses/by/4.0/http://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://bibliotecadigital.unipb.pt/bitstreams/16442f87-768a-45f2-a552-fb63200e4065/downloadMachine Learning and Deep Learning in Real- Time Applications132 |
| spellingShingle | Obtaining deep learning models for automatic classification of leukocytes Rodrigues, Pedro João Deep learning Leukocytes |
| status | SINGLETON |
| subject.fl_str_mv | Deep learning Leukocytes |
| title | Obtaining deep learning models for automatic classification of leukocytes |
| title_full | Obtaining deep learning models for automatic classification of leukocytes |
| title_fullStr | Obtaining deep learning models for automatic classification of leukocytes |
| title_full_unstemmed | Obtaining deep learning models for automatic classification of leukocytes |
| title_short | Obtaining deep learning models for automatic classification of leukocytes |
| title_sort | Obtaining deep learning models for automatic classification of leukocytes |
| topic | Deep learning Leukocytes |
| topic_facet | Deep learning Leukocytes |
| url | http://hdl.handle.net/10198/22527 |
| visible | 1 |
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