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[{"key": "dc.contributor.advisor", "value": "H\u00e4m\u00e4l\u00e4inen, Timo", "language": "", "element": "contributor", "qualifier": "advisor", "schema": "dc"}, {"key": "dc.contributor.advisor", "value": "Eskelinen Matti", "language": "", "element": "contributor", "qualifier": "advisor", "schema": "dc"}, {"key": "dc.contributor.advisor", "value": "K\u00e4rkk\u00e4inen Tommi", "language": "", "element": "contributor", "qualifier": "advisor", "schema": "dc"}, {"key": "dc.contributor.author", "value": "K\u00e4rkk\u00e4inen, Sonja", "language": null, "element": "contributor", "qualifier": "author", "schema": "dc"}, {"key": "dc.date.accessioned", "value": "2016-08-23T11:03:10Z", "language": "", "element": "date", "qualifier": "accessioned", "schema": "dc"}, {"key": "dc.date.available", "value": "2016-08-23T11:03:10Z", "language": "", "element": "date", "qualifier": "available", "schema": "dc"}, {"key": "dc.date.issued", "value": "2016", "language": null, "element": "date", "qualifier": "issued", "schema": "dc"}, {"key": "dc.identifier.other", "value": "oai:jykdok.linneanet.fi:1572232", "language": null, "element": "identifier", "qualifier": "other", "schema": "dc"}, {"key": "dc.identifier.uri", "value": "https://jyx.jyu.fi/handle/123456789/51007", "language": "", "element": "identifier", "qualifier": "uri", "schema": "dc"}, {"key": "dc.description.abstract", "value": "T\u00e4ss\u00e4 pro gradu -tutkielmassa selvitettiin ihmisten kiinnostusta konen\u00e4k\u00f6menetelm\u00e4ll\u00e4 koirarotuja tunnistavaan mobiilisovellukseen sek\u00e4 millaisia ominaisuuksia ihmiset haluavat t\u00e4lt\u00e4 sovellukselta. Konen\u00e4k\u00f6menetelmi\u00e4, joilla voi tunnistaa koirarotuja, on tutkittu vasta kuudessa aiemmassa tutkimuksessa. Ainoastaan yhdell\u00e4 mobiilisovelluksella on mahdollista tunnistaa koirarotuja, mutta sen toiminta perustuu hakukonelogiikkaan. Ihmisten kiinnostusta konen\u00e4k\u00f6menetelm\u00e4ll\u00e4 teht\u00e4v\u00e4\u00e4n koirarotujen tunnistamiseen, heid\u00e4n mielipiteit\u00e4\u00e4n siit\u00e4 sek\u00e4 millaisia ominaisuuksia mobiilisovelluksessa tulisi olla, selvitettiin survey-tutkimuksen kyselylomakkeella Facebookissa. Saatua m\u00e4\u00e4r\u00e4llist\u00e4 aineistoa analysoitiin tilastollisten menetelmien avulla. Avoimien kysymyksien vastauksia analysoitiin esimerkiksi ryhmittelem\u00e4ll\u00e4 tietoja. Tutkimuksen tulosten pohjalta on tarkoituksena alkaa suunnitella koirarotuja tunnistavaa sovellusta ja selvitt\u00e4\u00e4 siihen tarvittavia asioita esimerkiksi toiminnallisuuden ja k\u00e4ytett\u00e4vyyden osalta. Tutkimuksessa selvitettiin my\u00f6s, mitk\u00e4 kolme mobiilik\u00e4ytt\u00f6j\u00e4rjestelm\u00e4\u00e4 ovat parhaiten menestyneet markkinoilla, ja mik\u00e4 niist\u00e4 olisi paras suunniteltavalle sovellukselle. Survey-tutkimuksen avulla saatiin kuusi ominaisuutta, joita vastaajat pitiv\u00e4t t\u00e4rkein\u00e4 suunniteltavalle mobiilisovellukselle. N\u00e4m\u00e4 olivat: maksuttomuus, helppok\u00e4ytt\u00f6isyys, rotutiedot, oikea totuudenmukainen tieto, muu koiriin liittyv\u00e4 tieto ja toimivuus sek\u00e4 ryhmittym\u00e4, joka ei tiennyt tai ei kokenut kiinnostavana suunniteltavaa koirasovellusta. Tutkimuksen perusteella ihmiset ovat kiinnostuneita sovelluksesta, jolla on mahdollista tunnistaa koirarotuja. Vertailemalla kuutta eri konen\u00e4k\u00f6menetelm\u00e4\u00e4 huomataan, ett\u00e4 alueellisten maamerkkien avulla teht\u00e4v\u00e4 koirarotujen tunnistus lis\u00e4kysymysten avulla on paras mahdollinen menetelm\u00e4 niist\u00e4. Survey-tutkimuksen avulla sek\u00e4 tutkimalla esimerkiksi tieteellisi\u00e4 artikkeleita saatiin kokonaisk\u00e4sityst\u00e4 siit\u00e4, millaisia asioita on otettava huomioon suunniteltaessa mobiilisovellusta, jolla tunnistetaan koirarotuja konen\u00e4k\u00f6menetelm\u00e4ll\u00e4.", "language": "fi", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.abstract", "value": "This thesis clarified how people are interested in recognizing dog breeds with mobile application using computer vision and features, which people are looking forwards. The computer vision method support recognition of the dog breeds, have been previously analyzed in only six different researches. The only one of mobile application recognizes the dog breeds whose functions base on the logic of the search engine. The survey questionnaire was clarified on Face-book, how people are interested in recognizing dog breeds with the computer vision methods and their opinions related to the application and what kind of features should be developed in mobile application. The results of the quantitative method were analyzed with statistical methods. The answers of open questions were analyzed to group knowledge which interviewees think so important to the dog recognition application. Obtained results were used to design the application and solve issues related to working functionality and usability. This research also clarified three mobile operating systems, which has been the best in the mobile market, and what mobile platform is the best for application development, which should be designed in this research. The survey research found out six features that respondents think they are important to design mobile application. There are: free of charge, easy of use, the breed of knowledge, right truthful knowledge, other dog associated knowledge, functionality and one group who do not know what dog recognition application or are non-interest in designing dog application. The results of the survey research revealed conceptions which are listed as what way dog breed should be recognized on mobile application and what kind of thing should be designed with computer vision perceived for the theoretical background. The research found out that people are interested in mobile application, which can recognize dog breeds. Six different computer vision methods were compared based on computer vision. This comparison will reveal the best method of recognizing dog breeds on mobile application that was classified via landmarks with define questions. The survey research and science articles have provided useful information about what kind of thing should be perceived when designing mobile application using computer vision for dog breed recognition.", "language": "en", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Submitted using Plone Publishing form by Sonja K\u00e4rkk\u00e4inen (soilkark) on 2016-08-23 11:03:09.770200. Form: Pro gradu -lomake (https://kirjasto.jyu.fi/julkaisut/julkaisulomakkeet/pro-gradu-lomake). JyX data: [jyx_publishing-allowed (fi) =True]", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Submitted by jyx lomake-julkaisija (jyx-julkaisija.group@korppi.jyu.fi) on 2016-08-23T11:03:10Z\r\nNo. of bitstreams: 2\r\nURN:NBN:fi:jyu-201608233850.pdf: 1857158 bytes, checksum: 5cc199599523027c1c59f85d45617f8b (MD5)\r\nlicense.html: 4847 bytes, checksum: ec9b0ef988150090f2592a53816199c4 (MD5)", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Made available in DSpace on 2016-08-23T11:03:10Z (GMT). No. of bitstreams: 2\r\nURN:NBN:fi:jyu-201608233850.pdf: 1857158 bytes, checksum: 5cc199599523027c1c59f85d45617f8b (MD5)\r\nlicense.html: 4847 bytes, checksum: ec9b0ef988150090f2592a53816199c4 (MD5)\r\n Previous issue date: 2016", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.format.extent", "value": "1 verkkoaineisto (119 sivua)", "language": null, "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": "koira", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", 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