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Showing result 1 - 5 of 39 essays matching the above criteria.
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1. 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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2. Modulating Depth Map Features to Estimate 3D Human Pose via Multi-Task Variational Autoencoders
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Human pose estimation (HPE) constitutes a fundamental problem within the domain of computer vision, finding applications in diverse fields like motion analysis and human-computer interaction. This paper introduces innovative methodologies aimed at enhancing the accuracy and robustness of 3D joint estimation. READ MORE
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3. Knowledge distillation for anomaly detection
University essay from Uppsala universitet/Institutionen för informationsteknologiAbstract : The implementation of systems and methodologies for time series anomaly detection holds the potential of providing timely detection of faults and issues in a wide variety of technical systems. Ideally, these systems are able to identify deviations from the normal behavior of systems even before any problems manifest, thus enabling proactive maintenance. READ MORE
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4. Fault Detection and Diagnosis for Automotive Camera using Unsupervised Learning
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : This thesis aims to investigate a fault detection and diagnosis system for automotive cameras using unsupervised learning. 1) Can a front-looking wide-angle camera image dataset be created using Hardware-in-Loop (HIL) simulations? 2) Can an Adversarial Autoencoder (AAE) based unsupervised camera fault detection and diagnosis method be crafted for SPA2 Vehicle Control Unit (VCU) using an image dataset created using Hardware-inLoop? 3) Does using AAE surpass the performance of using Variational Autoencoder (VAE) for the unsupervised automotive camera fault diagnosis model? In the field of camera fault studies, automotive cameras stand out for its complex operational context, particularly in Advanced Driver-Assistance Systems (ADAS) applications. READ MORE
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5. Deep convolution neural network for attention decoding in multi-channel EEG with conditional variational autoencoder for data augmentation
University essay from Lunds universitet/Institutionen för reglerteknikAbstract : Objectives: This project aims to develop a deep learning-based attention decoding system that can distinguish between noise and speech in noise and also identify the direction of attended speech from the brain data recorded with electroencephalography (EEG) instruments. Two deep convolutional neural network (DCNN) models will be designed: (1) one DCNN model capable of classifying incoming segments of sound as speech or speech in background noise, and (2) one DCNN model identifying the direction (left vs. READ MORE
