Sökning: "Faltande Neurala Nätverk"

Hittade 3 uppsatser innehållade orden Faltande Neurala Nätverk.

  1. 1. Hyperparameter optimisation using Q-learning based algorithms

    Master-uppsats, Karlstads universitet/Fakulteten för hälsa, natur- och teknikvetenskap (from 2013)

    Författare :Daniel Karlsson; [2020]
    Nyckelord :Hyperparameter optimisation; Reinforcement learning; Convolutional neural networks; Hyperparameteroptimering; Förstärkningsinlärning; Faltande neurala nätverk;

    Sammanfattning : Machine learning algorithms have many applications, both for academic and industrial purposes. Examples of applications are classification of diffraction patterns in materials science and classification of properties in chemical compounds within the pharmaceutical industry. LÄS MER

  2. 2. A Reward-based Algorithm for Hyperparameter Optimization of Neural Networks

    Master-uppsats, Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)

    Författare :Olov Larsson; [2020]
    Nyckelord :Convolutional Neural Networks; Reinforcement Learning; Hyperparameter Optimization; Faltande Neurala Nätverk; Förstärkningsinlärning; Hyperparameteroptimering;

    Sammanfattning : Machine learning and its wide range of applications is becoming increasingly prevalent in both academia and industry. This thesis will focus on the two machine learning methods convolutional neural networks and reinforcement learning. LÄS MER

  3. 3. Object Tracking Achieved by Implementing Predictive Methods with Static Object Detectors Trained on the Single Shot Detector Inception V2 Network

    Master-uppsats, Karlstads universitet/Fakulteten för hälsa, natur- och teknikvetenskap (from 2013)

    Författare :Richard Dan William Barkman; [2019]
    Nyckelord :Supervised Machine Learning; Hyperparameter Optimisation; Convolutional Neural Networks; Lagrangian Mechanics; Predictive Methods;

    Sammanfattning : In this work, the possibility of realising object tracking by implementing predictive methods with static object detectors is explored. The static object detectors are obtained as models trained on a machine learning algorithm, or in other words, a deep neural network. LÄS MER