Sökning: "fine art"
Visar resultat 21 - 25 av 154 uppsatser innehållade orden fine art.
21. Enhancing failure prediction from timeseries histogram data : through fine-tuned lower-dimensional representations
Master-uppsats, Högskolan i Halmstad/Akademin för informationsteknologiSammanfattning : Histogram data are widely used for compressing high-frequency time-series signals due to their ability to capture distributional informa-tion. However, this compression comes at the cost of increased di-mensionality and loss of contextual details from the original features. LÄS MER
22. Multi-Label Toxic Comment Classification Using Machine Learning: An In-Depth Study
Master-uppsats, Lunds universitet/Institutionen för datavetenskapSammanfattning : The classification of toxic comments is a well-researched area with many techniques available. However, effectively managing multi-label categorization still requires a considerable amount of work. LÄS MER
23. A visual approach to web information extraction : Extracting information from e-commerce web pages using object detection
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Internets enorma omfattning har resulterat i ett överflöd av information som är oorganiserad och spridd över olika hemsidor. Det har varit motivationen för automatisk informationsextraktion av hemsidor sedan internets begynnelse. LÄS MER
24. ”Jag kan inte säga att jag lärde mig något nytt… ” En fenomenologisk intervjustudie om distansundervisning i Bildämnet på gymnasienivå
Kandidat-uppsats, Göteborgs universitet/HDK-Valand - Högskolan för konst och designSammanfattning : Earlier research show that students during the Covid-19 pandemic were greatly affected by the subsequent implementation of distance education in upper-secondary school throughout Sweden. This study aims to explore students’ experiences of distance education, specifically related to the subject of Visual Art. LÄS MER
25. Multilingual Transformer Models for Maltese Named Entity Recognition
Master-uppsats, Uppsala universitet/Institutionen för lingvistik och filologiSammanfattning : The recently developed state-of-the-art models for Named Entity Recognition are heavily dependent upon huge amounts of available annotated data. Consequently, it is extremely challenging for data-scarce languages to obtain significant result. LÄS MER