Sökning: "machine learning"

Visar resultat 1 - 5 av 2141 uppsatser innehållade orden machine learning.

  1. 1. 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

  2. 2. Data-driven configuration recommendation for microwave networks A comparison of machine learning approaches for the recommendation of configurations and the detection of configuration anomalies

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

    Författare :Simon Pütz; Simon Hallborn; [2020-11-06]
    Nyckelord :Configuration; Recommendation; Machine learning; Microwave network;

    Sammanfattning : As mobile networks grow and the demand for faster connections and a better reachabilityincreases, telecommunication providers are looking ahead to an increasingeffort to maintain and plan their networks. It is therefore of interest to avoid manualmaintenance and planning of mobile networks and look into possibilities to helpautomate such processes. LÄS MER

  3. 3. 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

  4. 4. Deep Learning for Deep Water: Robust classification of ship wakes with expert in the loop

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

    Författare :Igor RYAZANOV; [2020-10-06]
    Nyckelord :machine learning; deep learning; pattern recognition; acoustic data analysis; shipping data; data augmentation; noise robustness; classification with data imbalance; expert-in-the-loop framework;

    Sammanfattning : This work examines the applicability of the deep learning models to pattern recognitionin acoustic ocean data. The features of the dataset include noise, data scarcityand the lack of labeled samples. A deep learning model is proposed for the task ofautomatic wake detection. LÄS MER

  5. 5. Determining linguistic predictor for the classification of subjective cognitive impairment and mild cognitive impairment using machine learning

    Master-uppsats, Göteborgs universitet / Institutionen för filosofi, lingvistik och vetenskapsteori

    Författare :Tian Wang; [2020-09-01]
    Nyckelord :mild cognitive impairment; sibjective cognitive impairment; natural language processing; support vector machine; neural networks;

    Sammanfattning : Introduction Mild Cognitive Impairment (MCI) is a neurological condition characterized by cognitive decline greater than expected for an individual's age and education level. Subjective Cognitive Impairment (SCI) is a selfreported decline in cognitive abilities but not clinically identified as MCI. LÄS MER