Sökning: "informationsteknik"
Visar resultat 16 - 20 av 2081 uppsatser innehållade ordet informationsteknik.
16. Agda on Raspberry Pi
Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknikSammanfattning : This thesis presents an Agda-to-C compiler targeting the Raspberry Pi Pico microcontroller. The compiler implementation includes an unusual choice of run-time algorithm, a Foreign Function Interface generator, and surprisingly little boilerplate code... LÄS MER
17. Method and Tooling for Automated Conformance Checking between Architecture - design and Implementation
Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknikSammanfattning : Many software and/or automotive companies use UML models to write the requirements and later they are implemented by coding. Involving multiple engineers from different teams makes the whole process complex and cumbersome. LÄS MER
18. The Impact of Deep Neural Network Pruning on the Hyperparameter Performance Space: An Empirical Study
Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknikSammanfattning : With the continued growth of deep learning models in terms of size and computational requirements, the need for efficient models for deployment on resource-constrained devices becomes crucial. Structured pruning has emerged as a proven method to speed up models and reduce computational requirements. LÄS MER
19. Image Quality Assessment Pipeline and Semi-Automated Annotation method for Synthetic Data
Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknikSammanfattning : Predicting human emotions through facial expression, particularly in relation to medication field such as clinical trial settings, has garnered scientific interest in recent years due to significant understanding of the impact of treatment on emotions and social functioning. This thesis aims to improve performance of a FER model using large scale of synthetic data. LÄS MER
20. A type-driven approach for sensitivity checking with branching
Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknikSammanfattning : Differential Privacy (DP) is a promising approach to allow privacy preserving statistics over large datasets of sensitive data. It works by adding random noise to the result of the analytics. Understanding the sensitivity of a query is key to add the right amount of noise capable of protecting privacy of individuals in the dataset. LÄS MER