Essays about: "Synthetic Dataset"
Showing result 1 - 5 of 138 essays containing the words Synthetic Dataset.
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1. Using Synthetic Data For Object Detection on the edge in Hazardous Environments
University essay from Lunds universitet/Institutionen för reglerteknikAbstract : This thesis aims to evaluate which aspects are important when generating synthetic data with the purpose of running on a lightweight object detection model on an edge device. The task we constructed was to detect Canisters and whether they feature a protective valve called a Cap or not (called a No-Cap). READ MORE
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2. Variational AutoEncoders and Differential Privacy : balancing data synthesis and privacy constraints
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : This thesis investigates the effectiveness of Tabular Variational Auto Encoders (TVAEs) in generating high-quality synthetic tabular data and assesses their compliance with differential privacy principles. The study shows that while TVAEs are better than VAEs at generating synthetic data that faithfully reproduces the distribution of real data as measured by the Synthetic Data Vault (SDV) metrics, the latter does not guarantee that the synthetic data is up to the task in practical industrial applications. READ MORE
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3. Measuring the Utility of Synthetic Data : An Empirical Evaluation of Population Fidelity Measures as Indicators of Synthetic Data Utility in Classification Tasks
University essay from Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)Abstract : 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. READ MORE
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4. AI-based image generation: The impact of fine-tuning on fake image detection
University essay from Stockholms universitet/Institutionen för data- och systemvetenskapAbstract : Machine learning-based image generation models such as Stable Diffusion are now capable of generating synthetic images that are difficult to distinguish from real images, which gives rise to a number of legal and ethical concerns. As a potential measure of mitigation, it is possible to train neural networks to detect the digital artifacts present in the images synthesized by many generative models. READ MORE
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5. Improving echocardiogram view classification using diffusion models
University essay from Göteborgs universitet/Institutionen för data- och informationsteknikAbstract : In the field of medical science datasets are often highly imbalanced, where rare datapoints are of high importance. This study aims to explore the usage of synthetic datasets to improve the classification of echocardiogram views. READ MORE
