Please use this identifier to cite or link to this item: http://thuvienso.dut.udn.vn/handle/DUT/5511
DC FieldValueLanguage
dc.contributor.advisorPGS. TS Phạm, Văn Tuấnen_US
dc.contributor.advisorDoan, Thanh Thienen_US
dc.contributor.authorLê, Ngọc Hảien_US
dc.contributor.authorDương, Nguyễn Huy Thứcen_US
dc.contributor.authorNguyễn, Quang Sangen_US
dc.date.accessioned2025-02-15T08:23:03Z-
dc.date.available2025-02-15T08:23:03Z-
dc.date.issued2019-
dc.identifier.urihttp://thuvienso.dut.udn.vn/handle/DUT/5511-
dc.description69 Tr.en_US
dc.description.abstractFor the Manufacturing line of any company, it’s essential that the products are carefully checked after their fabrication. The same rule is applied to Fossil. For Fossil’s Manufacturing Line, ATE stations play an important role. These stations are in charge of making sure that every watch which is under test operate well before its release to the market The current ATE system used in Fossil’s manufacturing line has been working stably for a period of time. However, as the heart of ATE, Raspberry Pi 3, has to take care of all tasks required, it’s just an natural idea that we can optimize the performance and efficiency of the system, by sharing some important tasks which account a great amount of resource with another module. The main demand of out project is to implement such module to be integrated in ATE systemen_US
dc.language.isoenen_US
dc.publisherTrường Đại học Bách khoa - Đại học Đà Nẵngen_US
dc.subjectComputer visionen_US
dc.subjectFossil’sen_US
dc.titleResearch and develop Computer Vision module for Fossil’s manufacturing Lineen_US
dc.typeĐồ ánen_US
dc.identifier.id2.DA.FA.19.003-
item.grantfulltextrestricted-
item.openairetypeĐồ án-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.fulltextCó toàn văn-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
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