Sökning: "Hybrid Network"
Visar resultat 6 - 10 av 204 uppsatser innehållade orden Hybrid Network.
6. Investigating the density evolution of charged particles inside a square domain
L3-uppsats, Uppsala universitet/Institutionen för fysik och astronomiSammanfattning : In this work, I propose a hybrid particle simulator for charged particles. The simulator consists of a physics-informed neural network, which can handle arbitrary external electric fields with continuous coordinates by solving the Poisson equation, and a graph-based algorithm that computes the interacting forces between the particles. LÄS MER
7. Exploring the Advantages, Disadvantages, and Challenges of Implementing a Hybrid LiFi and WiFi Network : A Systematic Literature Review
Kandidat-uppsats, Högskolan i Skövde/Institutionen för informationsteknologiSammanfattning : I takt med att efterfrågan på trådlös kommunikation med hög hastighet ökar och det ökande antalet enheter som är trådlöst anslutna har forskare börjat utforska kompletterande teknologier. Hybridnätverk bestående av LiFi och WiFi är en kombination av Light-Fidelity och Wireless-Fidelity som kombinerar dataöverföring över både radiovågor och ljus. LÄS MER
8. Quantum Reinforcement Learning for Sensor-Assisted Robot Navigation Tasks
Master-uppsats, Lunds universitet/Fysiska institutionenSammanfattning : Quantum computing has advanced rapidly throughout the past decade, both from a hardware and software point of view. A variety of algorithms have been developed that are suitable for the current generation of quantum devices, which are referred to as noisy intermediate-scale quantum devices. LÄS MER
9. Hybrid Deep Learning approach for Lane Detection : Combining convolutional and transformer networks with a post-processing temporal information mechanism, for efficient road lane detection on a road image scene
Master-uppsats, Jönköping University/Jönköping AI Lab (JAIL)Sammanfattning : Lane detection is a crucial task in the field of autonomous driving and advanced driver assistance systems. In recent years, convolutional neural networks (CNNs) have been the primary approach for solving this problem. LÄS MER
10. EVALUATING PERFORMANCE OF GENERATIVE MODELS FOR TIME SERIES SYNTHESIS
Master-uppsats, Mälardalens universitet/Akademin för innovation, design och teknikSammanfattning : Motivated by successes in the image generation domain, this thesis presents a novel Hybrid VQ-VAE (H-VQ-VAE) approach for generating realistic synthetic time series data with categorical features. The primary motivation behind this work is to address the limitations of existing generative models in accurately capturing the underlying structure and patterns of time series data, especially when dealing with categorical features. LÄS MER