Sökning: "Neural network"

Visar resultat 1 - 5 av 1241 uppsatser innehållade orden Neural network.

  1. 1. Generative Neural Network for Portfolio Optimization

    Master-uppsats, Mälardalens högskola/Akademin för utbildning, kultur och kommunikation

    Författare :Mengxin Liu; [2021]
    Nyckelord :GAN; Portfolio Optimization; Neural Networks;

    Sammanfattning : This thesis aims to overcome the drawbacks of traditional portfolio optimization by employing Generative Deep Neural Networks on real stock data. The proposed framework is capable of generating return data that have similar statistical characteristics as the original stock data. LÄS MER

  2. 2. Convolutional neural networks for semantic segmentation of FIB-SEM volumetric image data

    Master-uppsats, Göteborgs universitet/Institutionen för matematiska vetenskaper

    Författare :Fredrik Skärberg; [2020-11-26]
    Nyckelord :Deep learning; convolutional neural networks; image analysis; semantic segmentation; focused ion beam scanning electron microscopy; porous materials; controlled drug release;

    Sammanfattning : Focused ion beam scanning electron microscopy (FIB-SEM) is a well-established microscopytechnique for 3D imaging of porous materials. We investigate three poroussamples of ethyl cellulose microporous films made from ethyl cellulose and hydroxypropylcellulose (EC/HPC) polymer blends. LÄS MER

  3. 3. Interactionwise Semantic Awareness in Visual Relationship Detection

    Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

    Författare :Pagliarini Giovanni; Imtiaz Azfar; [2020-11-06]
    Nyckelord :Deep Learning; Natural Language Processing; Computer Vision; Visual Relationship Detection; Object Detection;

    Sammanfattning : Visual Relationship Detection (VRD) is a relatively young research area, where thegoal is to develop prediction models for detecting the relationships between objectsdepicted in an image. A relationship is modeled as a subject-predicate-object triplet,where the predicate (e.g an action, a spatial relation, etc. LÄS MER

  4. 4. Clustering and Classification of Time Series in Real-Time Strategy Games - A machine learning approach for mapping StarCraft II games to clusters of game state time series while limited by fog of war

    Kandidat-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

    Författare :Olof Enström; Fredrik Hagström; John Segerstedt; Fredrik Viberg; Arvid Wartenberg; David Weber Fors; [2020-10-29]
    Nyckelord :Classification problem; Cluster analysis; Hierarchical clustering; Machine learning; Neural network; Random forest; Real-time strategy; StarCraft II; Time series;

    Sammanfattning : Real-time strategy (RTS) games feature vast action spaces and incomplete information,thus requiring lengthy training times for AI-agents to master them at the level of ahuman expert. Based on the inherent complexity and the strategical interplay betweenthe players of an RTS game, it is hypothesized that data sets of played games exhibitclustering properties as a result of the actions made by the players. LÄS MER

  5. 5. Resource Optimal Neural Networks for Safety-critical Real-time Systems

    Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

    Författare :Joakim Åkerström; [2020-07-10]
    Nyckelord :Data science; machine learning; deep learning; neural networks; network compression; network acceleration; safety-critical systems; real-time systems;

    Sammanfattning : Deep neural networks consume an excessive amount of hardware resources, makingthem difficult to deploy to real-time systems. Previous work in the field of networkcompression lack the explicit hardware feedback necessary to control the resourceconstraints imposed by such systems. LÄS MER