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Visar resultat 1 - 5 av 231 uppsatser som matchar ovanstående sökkriterier.

1. 1. Modulating Depth Map Features to Estimate 3D Human Pose via Multi-Task Variational Autoencoders

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Kobe Moerman; [2023]
   Nyckelord :3D pose estimation; Joint landmarks; Variational autoencoder; Multi-task model; Loss discrimination; Latent-space modulation; Depth map; 3D-positionsuppskattning; Gemensamma landmärken; Variationell autoencoder; Multitask-modell; Förlustdiskriminering; Latent-space-modulering; Djupkarta;

   Sammanfattning : 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. LÄS MER

3. 2. Robust Aircraft Positioning using Signals of Opportunity with Direction of Arrival

   Master-uppsats, Linköpings universitet/Reglerteknik

   Författare :Erik Axelsson; Sebastian Fagerstedt; [2023]
   Nyckelord :Simultaneous localisation and mapping; direction of arrival; signals of opportunity; extended Kalman filter; positioning;

   Sammanfattning : This thesis considers the problem of using signals of opportunity (SOO) with known direction of arrival (DOA) for aircraft positioning. SOO is a collective name for a wide range of signals not intended for navigation but which can be intercepted by the radar warning system on an aircraft. LÄS MER

4. 3. Dynamic Object Removal for Point Cloud Map Creation in Autonomous Driving : Enhancing Map Accuracy via Two-Stage Offline Model

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Weikai Zhou; [2023]
   Nyckelord :Autonomous driving; Dynamic object removal; Map creation; 3D point cloud; Autonom körning; Dynamiska objekt borttagning; Skapande av kartor; 3D-punktmoln;

   Sammanfattning : Autonomous driving is an emerging area that has been receiving an increasing amount of interest from different companies and researchers. 3D point cloud map is a significant foundation of autonomous driving as it provides essential information for localization and environment perception. LÄS MER

5. 4. Filtering Pressure Oscillations in a Common Rail Pressure Signal with IIR Notch Filters for Injected Fuel Amount Estimation

   Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)

   Författare :Marcus Akkila; Denis Ramsden; [2023]
   Nyckelord :DSP; Water hammer effect; IIR; Common-rail; Injected fuel amount estimation; Notch filter; Water hammer effect; IIR; Digital signalbehandling; Injektionsmängd; Common-rail; bandstoppfilter;

   Sammanfattning : This project concerns an inline six-cylinder (I6) diesel truck engine equipped with common-rail injection system. It has been done at the Swedish truck manufacturer Scania CV AB. The main focus is digital signal processing of the rail pressure sensor signal from the injection system. LÄS MER

7. 5. Robust Non-Linear State Estimation for Underwater Acoustic Localization : Expanding on Gaussian Mixture Methods

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Diogo Antunes; [2023]
   Nyckelord :Robust state estimation; Underwater localization; Target tracking; Gaussian mixture; AUV; Estimação robusta de estado; Localização subaquática; Rastreamento de alvos; Mistura Gaussiana; AUV; Robust tillståndsuppskattning; Undervattenslokalisering; Målspårning; Gaussisk blandning; AUV;

   Sammanfattning : Robust state estimation solutions must deal with faulty measurements, called outliers, and unknown data associations, which lead to multiple feasible hypotheses. Take, for instance, the scenario of tracking two indistinguishable targets based on position measurements, where each measurement could refer to either of the targets or even be a faulty reading. LÄS MER