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[{"key": "dc.contributor.advisor", "value": "Matti, Eskelinen", "language": "", "element": "contributor", "qualifier": "advisor", "schema": "dc"}, {"key": "dc.contributor.advisor", "value": "Paavo, Nieminen", "language": "", "element": "contributor", "qualifier": "advisor", "schema": "dc"}, {"key": "dc.contributor.author", "value": "Juuti, Tanja", "language": "", "element": "contributor", "qualifier": "author", "schema": "dc"}, {"key": "dc.date.accessioned", "value": "2018-11-28T06:28:37Z", "language": null, "element": "date", "qualifier": "accessioned", "schema": "dc"}, {"key": "dc.date.available", "value": "2018-11-28T06:28:37Z", "language": null, "element": "date", "qualifier": "available", "schema": "dc"}, {"key": "dc.date.issued", "value": "2018", "language": "", "element": "date", "qualifier": "issued", "schema": "dc"}, {"key": "dc.identifier.uri", "value": "https://jyx.jyu.fi/handle/123456789/60354", "language": null, "element": "identifier", "qualifier": "uri", "schema": "dc"}, {"key": "dc.description.abstract", "value": "Suomen ymp\u00e4rist\u00f6hallinnossa on alettu viime vuosina kiinnostua enenev\u00e4ss\u00e4 m\u00e4\u00e4rin konen\u00e4\u00f6n hy\u00f6dynt\u00e4misest\u00e4 lajintunnistuksessa. Esimerkiksi tienvarsien haittakasvilajeja on tunnistettu varsin hyvin tuloksin. Koneellinen, lajeja tunnistava luokittelija voidaan toteuttaa esimerkiksi Bayes-verkoilla. Ne ovat todenn\u00e4k\u00f6isyysmalleja, joilla voidaan mallintaa muuttujien v\u00e4lisi\u00e4 riippuvuuksia. Rakenteeltaan erilaiset Bayes-luokittelijat pystyv\u00e4t eri tavoin huomioimaan piirremuuttujien v\u00e4lisi\u00e4 riippuvuuksia. Esimerkiksi naiivi Bayes-menetelm\u00e4 olettaa piirremuuttujien riippuvan ainoastaan lajiluokasta. Tutkimuksen tavoitteena olikin selvitt\u00e4\u00e4, millainen Bayes-verkko olisi sopiva luokittelija kukkivien kasvien lajintunnistukseen. Tunnistuskohteeksi valittiin kukat, koska ne ovat monimuotoisuutensa ja erottuvuutensa vuoksi hyvi\u00e4 kohteita elinymp\u00e4rist\u00f6ss\u00e4\u00e4n kuvattujen kasvien konen\u00e4\u00f6lliseen lajintunnistukseen. Kukkien v\u00e4ri\u00e4 kuvattiin v\u00e4rihistogrammien tilastollisilla tunnusluvuilla ja muotoa kuvamomenteilla sek\u00e4 skaalainvarianteilla pistepiirteill\u00e4. Lis\u00e4ksi kukista m\u00e4\u00e4ritettiin ter\u00e4lehtien sijaintia ja kokoa kuvaavia piirteit\u00e4. Luokittelutulosten perusteella kuvista lasketut piirteet kuvasivat hyvin tutkimuksessa mukana olleiden lajien v\u00e4lisi\u00e4 eroja. Sen sijaan piirremuuttujien riippuvuuksia huomioivat luokittelumallit eiv\u00e4t tuottaneet naiivia mallia parempia tuloksia. Onkin osoitettu, ett\u00e4 tietynlaisissa riippuvuustilanteissa naiivi luokittelija on riippuvuutta huomioivien mallien veroinen. Riitt\u00e4v\u00e4n yksinkertaisena naiivi malli on my\u00f6s hyv\u00e4 yleismalli. Osa t\u00e4ss\u00e4 tutkimuksessa testatuista malleista oli liian monimutkaisia havaintojen m\u00e4\u00e4r\u00e4\u00e4n n\u00e4hden. Jatkossa tulisikin kiinnitt\u00e4\u00e4 erityishuomiota siihen, millainen piirremuuttujien diskretisointi ja mallin rakennusprosessi tuottavat riitt\u00e4v\u00e4n yksinkertaisen mutta hyv\u00e4n mallin.", "language": "fi", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.abstract", "value": "In recent years Finland's environmental administration has shown growing interest in utilizing computer vision in species recognition. As an example, good results have been achieved in identifying invasive plant species growing on roadsides. One option to build a classifier to recognize plant species is to use Bayesian networks, which are probability models that are able to model variable interdependencies. Different kinds of Bayesian classifiers have varying abilities to take into account the dependencies between feature variables. For example, naive Bayesian classifier is based on the assumption that the feature variables only depend on the object class. The aim of this study was to find out what kind of Bayesian network would be ideal in identifying flowering plant species. The images of flowers were used because the diversity and distinctness of flowers make them good targets for computer vision purposes. The color of the flower was represented by statistics of the color histogram and the shape of the flower was described with image moments and local scale-invariant features. Additional variables were extracted to represent the size and position of the petals. The classification results showed that the chosen features described the differences between the studied species quite well. However, the models taking into account the interdependencies of the feature variables did not yield any better results compared to the naive Bayesian classifier. In fact, other studies have showed that under certain dependence conditions the naive classifier can have discriminative power equal to the models that take the interdependencies into account. Naive Bayes is also simple enough to function as a good general model. Some models tested in this study were too complicated considering the small number of samples in the dataset. In future, special attention should be paid to how the feature variables should be discretized and how the model should be built in order to achieve a sufficiently simple but powerful model.", "language": "en", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Submitted by Paivi Vuorio (paelvuor@jyu.fi) on 2018-11-28T06:28:37Z\nNo. of bitstreams: 0", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Made available in DSpace on 2018-11-28T06:28:37Z (GMT). No. of bitstreams: 0\n Previous issue date: 2018", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.format.extent", "value": "120", "language": "", "element": "format", "qualifier": "extent", "schema": "dc"}, {"key": "dc.format.mimetype", "value": "application/pdf", "language": null, "element": "format", "qualifier": "mimetype", "schema": "dc"}, {"key": "dc.language.iso", "value": "fin", "language": null, "element": "language", "qualifier": "iso", "schema": "dc"}, {"key": "dc.rights", "value": "In Copyright", "language": "en", "element": "rights", "qualifier": null, "schema": "dc"}, {"key": "dc.subject.other", "value": "Bayes-verkko", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "naiivi Bayes-luokittelija", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "lajintunnistus", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "luokittelu", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.title", "value": "Bayesil\u00e4iset graa\ufb01set mallit konen\u00e4\u00f6ss\u00e4 : kukkivien kasvien lajintunnistus", "language": "", "element": "title", "qualifier": null, "schema": "dc"}, {"key": "dc.type", "value": "master thesis", "language": null, "element": "type", "qualifier": null, "schema": "dc"}, {"key": "dc.identifier.urn", "value": "URN:NBN:fi:jyu-201811284896", "language": "", "element": "identifier", "qualifier": "urn", "schema": "dc"}, {"key": "dc.type.ontasot", "value": "Pro gradu -tutkielma", "language": "fi", "element": "type", "qualifier": "ontasot", "schema": "dc"}, {"key": "dc.type.ontasot", "value": "Master\u2019s thesis", "language": "en", "element": "type", "qualifier": "ontasot", "schema": "dc"}, {"key": "dc.contributor.faculty", "value": "Informaatioteknologian tiedekunta", "language": "fi", "element": "contributor", "qualifier": "faculty", "schema": "dc"}, {"key": "dc.contributor.faculty", "value": "Faculty of Information Technology", "language": "en", "element": "contributor", "qualifier": "faculty", "schema": "dc"}, {"key": "dc.contributor.department", "value": "Informaatioteknologia", "language": "fi", "element": "contributor", "qualifier": "department", "schema": "dc"}, {"key": "dc.contributor.department", "value": "Information Technology", "language": "en", "element": "contributor", "qualifier": "department", "schema": "dc"}, {"key": "dc.contributor.organization", "value": "Jyv\u00e4skyl\u00e4n yliopisto", "language": "fi", "element": "contributor", "qualifier": "organization", "schema": "dc"}, {"key": "dc.contributor.organization", "value": "University of Jyv\u00e4skyl\u00e4", "language": "en", "element": "contributor", "qualifier": "organization", "schema": "dc"}, {"key": "dc.subject.discipline", "value": "Tietotekniikka", "language": "fi", "element": "subject", "qualifier": "discipline", "schema": "dc"}, {"key": "dc.subject.discipline", "value": "Mathematical Information Technology", "language": "en", "element": "subject", "qualifier": "discipline", "schema": "dc"}, {"key": "yvv.contractresearch.funding", "value": "0", "language": "", "element": "contractresearch", "qualifier": "funding", "schema": "yvv"}, {"key": "dc.type.coar", "value": "http://purl.org/coar/resource_type/c_bdcc", "language": null, "element": "type", "qualifier": "coar", "schema": "dc"}, {"key": "dc.rights.accesslevel", "value": "openAccess", "language": null, "element": "rights", "qualifier": "accesslevel", "schema": "dc"}, {"key": "dc.type.publication", "value": "masterThesis", "language": null, "element": "type", "qualifier": "publication", "schema": "dc"}, {"key": "dc.subject.oppiainekoodi", "value": "602", "language": "", "element": "subject", "qualifier": "oppiainekoodi", "schema": "dc"}, {"key": "dc.subject.yso", "value": "lajinm\u00e4\u00e4ritys", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "kasvit", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "koneoppiminen", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "konen\u00e4k\u00f6", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.format.content", "value": "fulltext", "language": null, "element": "format", "qualifier": "content", "schema": "dc"}, {"key": "dc.rights.url", "value": "https://rightsstatements.org/page/InC/1.0/", "language": null, "element": "rights", "qualifier": "url", "schema": "dc"}, {"key": "dc.type.okm", "value": "G2", "language": null, "element": "type", "qualifier": "okm", "schema": "dc"}]
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