Essays about: "Lärande i nätverk"

Showing result 1 - 5 of 82 essays containing the words Lärande i nätverk.

  1. 1. Adaptive Model-Based Temperature Monitoring for Electric Powertrains : Investigation and Comparative Analysis of Transfer Learning Approaches

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Chenzhou Huang; [2023]
    Keywords : Transfer Learning; Condition Monitoring; Domain Adaptation; Neural Network; Powerstrain.; Siirto-oppiminen; kunnonvalvonta; verkkotunnuksen mukauttaminen; neuroverkko; voimansiirto.; Överföring lärande; tillståndsövervakning; domänanpassning; neuralt nätverk; Powerstrain;

    Abstract : In recent years, deep learning has been widely used in industry to solve many complex problems such as condition monitoring and fault diagnosis. Powertrain condition monitoring is one of the most vital and complicated problems in the automation industry since the condition of the drive affects its health, performance, and reliability. READ MORE

  3. 2. Cooperative Modular Neural Networks for Artificial Intelligence in Games : A Comparison with A Monolithic Neural Network Regarding Technical Aspects and The Player Experience

    University essay from Blekinge Tekniska Högskola/Fakulteten för datavetenskaper

    Author : Emil Högstedt; Ove Ødegård; [2023]
    Keywords : Neural Network; Modularization; Sensor; Reinforcement Learning; Supervised Learning; Neuralt Nätverk; Modulärisering; Sensor; Förstärkningsinlärning; Väglett Lärande;

    Abstract : Recent years have seen multiple machine-learning research projects concerning agents in video games. Yet, there is a disjoint between this academic research and the video game industry, evidenced by the fact that game developers still hesitate to use neural networks (NN) due to lack of clarity and control. READ MORE

  4. 3. Fault Detection and Diagnosis for Automotive Camera using Unsupervised Learning

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Ziyou Li; [2023]
    Keywords : Unsupervised Learning; Autoencoders; Image Clustering; Fault Detection and Diagnosis; Morphological Operations; Hardware-in-Loop; Advanced DriverAssistance System; Oövervakad inlärning; Autoencoders; Bildklustering; Felfindning och Diagnostik; Morfologiska Operationer; Hardware-in-Loop; Avancerade Förarassistanssystem;

    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

  5. 4. Modelling synaptic rewiring in brain-like neural networks for representation learning

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Kunal Bhatnagar; [2023]
    Keywords : Adaptive Sparsity; Computational Neuroscience; Rewiring; Structural Plasticity; Brain-like Computing; Neural Networks; Hebbian Learning; Adaptiv gleshet; beräkningsneurovetenskap; omkoppling; strukturell plasticitet; Hjärnliknande beräkning; Neurala Nätverk; Hebbskt lärande;

    Abstract : This research investigated the concept of a sparsity method inspired by the principles of structural plasticity in the brain in order to create a sparse model of the Bayesian Confidence Propagation Neural Networks (BCPNN) during the training phase. This was done by extending the structural plasticity in the implementation of the BCPNN. READ MORE

  6. 5. Stabilizing Side Effects of Experience Replay With Different Network Sizes for Deep Q-Network

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Simon Granström; [2023]
    Keywords : ;

    Abstract : This report investigates the effects of two different types of batch selection used for traininga Deep Reinforcement Learning agent in games. More specifically, the impact of thedifferent methods were tested for different sizes of Deep Neural Networks while using theDeep Q-Network (DQN) algorithm. READ MORE