Sökning: "learning-based testing"
Visar resultat 1 - 5 av 34 uppsatser innehållade orden learning-based testing.
1. Measuring the Utility of Synthetic Data : An Empirical Evaluation of Population Fidelity Measures as Indicators of Synthetic Data Utility in Classification Tasks
Master-uppsats, Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)Sammanfattning : In the era of data-driven decision-making and innovation, synthetic data serves as a promising tool that bridges the need for vast datasets in machine learning (ML) and the imperative necessity of data privacy. By simulating real-world data while preserving privacy, synthetic data generators have become more prevalent instruments in AI and ML development. LÄS MER
2. Deep Learning-Based Anomaly Detection for Predictive Maintenance of Cold Isostatic Press
Master-uppsats, Mälardalens universitet/Akademin för innovation, design och teknikSammanfattning : Predictive maintenance is an automated technique that analyses sensor data from industrial systems to enable downtime planning. Available for this study is unlabelled data from sensors placed in proximity to hydraulic system outlets of a cold isostatic press. LÄS MER
3. Learning Based Road Estimation
Master-uppsats, Lunds universitet/Matematik LTHSammanfattning : The interest in autonomous driving has vastly increased, leading to a surge in research and development efforts over the past decades. This technology could enhance road safety, alleviate traffic congestion, and yield numerous environmental and economic benefits. LÄS MER
4. Individual Layer Scaling and Redundancy Reduction of Singleshot Multiplane Images for View Synthesis
Master-uppsats, Lunds universitet/Matematik LTHSammanfattning : Image-based rendering for view synthesis is a field within computer vision that has seen a growing number of research activity within the past few years, much due to deep learning techniques emerging, allowing researchers to re-format view synthesis as a learning problem. The multiplane image (MPI) is a recently proposed learning-based layered 3D representation, created from one or a few input images for the purpose of rendering novel views. LÄS MER
5. Error detection in blood work : Acomparison of self-supervised deep learning-based models
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Errors in medical testing may cause serious problems that has the potential to severely hurt patients. There are many machine learning methods to discover such errors. However, due to the rarity of errors, it is difficult to collect enough examples to learn from them. It is therefore important to focus on methods that do not require human labeling. LÄS MER