Sökning: "Hierarchy Clustering"

Visar resultat 1 - 5 av 12 uppsatser innehållade orden Hierarchy Clustering.

  1. 1. Model-Based versus Data-Driven Control Design for LEACH-based WSN

    Master-uppsats, KTH/Maskinkonstruktion (Inst.); KTH/Maskinkonstruktion (Inst.)

    Författare :Axel Karlsson; Bohan Zhou; [2020]
    Nyckelord :Wireless sensor network; mobile sink; LEACH; model predictive control; reinforcement learning; Deep Q-Networks; : Trådlösa sensor nätverk; LEACH; modellbaserad regulator; reinforcement learning; Deep Q-Networks;

    Sammanfattning : In relation to the increasing interest in implementing smart cities, deployment of widespread wireless sensor networks (WSNs) has become a current hot topic. Among the application’s greatest challenges, there is still progress to be made concerning energy consumption and quality of service. LÄS MER

  2. 2. Speaker Diarization System for Call-center data

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Yi Li; [2020]
    Nyckelord :MFCC-vector Speaker Diarization; Speaker Verification; Voice Active Detection; Gaussian Mixture Model; Hierarchy Clustering; MFCC-vektor Högtalardarisering; Högtalarverifiering; Röstaktiv detektering; Gaussisk blandningsmodell; Hierarkikluster;

    Sammanfattning : To answer the question who spoke when, speaker diarization (SD) is a critical step for many speech applications in practice. The task of our project is building a MFCC-vector based speaker diarization system on top of a speaker verification system (SV), which is an existing Call-centers application to check the customer’s identity from a phone call. LÄS MER

  3. 3. Hierarchical Clustering of Time Series using Gaussian Mixture Models and Variational Autoencoders

    Master-uppsats, Lunds universitet/Matematisk statistik

    Författare :Per Wilhelmsson; [2019]
    Nyckelord :Clustering; Deep Learning; Machine Learning; Time Series; Variational Autoencoders; Gaussian Mixture Models; Mathematics and Statistics;

    Sammanfattning : This thesis proposes a hierarchical clustering algorithm for time series, comprised of a variational autoencoder to compress the series and a Gaussian mixture model to merge them into an appropriate cluster hierarchy. This approach is motivated by the autoencoders good results in dimensionality reduction tasks and by the likelihood framework given by the Gaussian mixture model. LÄS MER

  4. 4. Multi-scale clustering in graphs using modularity

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Bertrand Charpentier; [2019]
    Nyckelord :Hierarchical clustering; Multi-scale clustering; Graph; Modularity; Resolution; Dendrogram;

    Sammanfattning : This thesis provides a new hierarchical clustering algorithm for graphs, named Paris, which can be interpreted through the modularity score and its resolution parameter. The algorithm is agglomerative and based on a simple distance between clusters induced by the probability of sampling node pairs. LÄS MER

  5. 5. Automatic Clustering of 3D Objects for Hierarchical Level-of-Detail

    Master-uppsats, Linköpings universitet/Medie- och InformationsteknikLinköpings universitet/Tekniska fakulteten

    Författare :Benjamin Wiberg; [2018]
    Nyckelord :hierarchical level-of-detail; mesh simplification; hierarchical clustering; 3D optimization;

    Sammanfattning : This report describes an algorithm for computing 3D object hierarchies fit for hlod optimization. The algorithm is used as a pre-processing stage in an hlod pipeline that automatically optimizes 3D models containing multiple meshes. LÄS MER