Sökning: "algorithmic classification"

Visar resultat 1 - 5 av 12 avhandlingar innehållade orden algorithmic classification.

  1. 1. An Algorithmic Framework for Intelligent Concrete Structural Defects Detection and Classification

    Författare :Ali Mirzazade; Björn Täljsten; Cosmin Popescu; Thomas Blanksvärd; Diogo Rodrigo Ferreira Ribeiro; Luleå tekniska universitet; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Civil Engineering Structures; defect detection; Structural Health Assessment; Bridge Inspection; Computer Vision; Point-Cloud Generation; Severity Assessment; Machine Learning Regression; Bridge 3D Modeling; Unmanned Inspections; Byggkonstruktion; Structural Engineering;

    Sammanfattning : The primary objective of inspecting concrete civil structures is to gather information concerning the deterioration of concrete elements, including issues like concrete cover cracking, delamination, or corrosion. Typically, this data is documented through field inspection notes, hand-drawn sketches, and photographs. LÄS MER

  3. 2. Spellistejournalistik : En studie av algoritmisk design, automatisering och journalistiska praktiker på Sveriges Radio

    Författare :Torbjörn Rolandsson; Andreas Widholm; Jörgen Behrendtz; Fredrik Stiernstedt; Stockholms universitet; []
    Nyckelord :HUMANIORA; HUMANITIES; algorithm; public service; cultural techniques; automation; technography; journalistic practice; Journalism; journalistik;

    Sammanfattning : This dissertation explores how a shift in the format of news distribution prompted changes in journalistic practices when the Public Service Media (PSM) organization Sveriges Radio (SR) started distributing news via digital playlists. Thereby, it provides much-needed empirical footing to the ongoing normative debates about how PSM should navigate a media landscape characterized by datafication, algorithmic technologies, and automation, in short, platformization. LÄS MER

  4. 3. Algorithms in data mining using matrix and tensor methods

    Författare :Berkant Savas; Lars Eldén; Lieven De Lathauwer; Linköpings universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Volume; Minimization criterion; Determinant; Rank deficient matrix; Reduced rank regression; System identification; Rank reduction; Volume minimization; General algorithm; Handwritten digit classification; Tensors; Higher order singular value decomposition; Tensor approximation; Least squares; Tucker model; Multilinear algebra; Notation; Contraction; Tensor matricization; Newton s method; Grassmann manifolds; Product manifolds; Quasi-Newton algorithms; BFGS and L-BFGS; Symmetric tensor approximation; Local intrinsic coordinates; Global embedded coordinates; ; Numerical analysis; Numerisk analys;

    Sammanfattning : In many fields of science, engineering, and economics large amounts of data are stored and there is a need to analyze these data in order to extract information for various purposes. Data mining is a general concept involving different tools for performing this kind of analysis. LÄS MER

  5. 4. Computer Vision for Traffic Surveillance Systems : Methods and Applications

    Författare :Saleh Javadi; Mattias Dahl; Michael Cree; Blekinge Tekniska Högskola; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; Intelligent transportation systems; ITS; Computer visions systems; Systemteknik; Systems Engineering;

    Sammanfattning : Computer vision solutions play a significant role in intelligent transportation systems (ITS) by improving traffic flow, safety and management. In addition, they feature prominently in autonomous vehicles and their future development. The main advantages of vision-based systems are their flexibility, coverage and accessibility. LÄS MER

  7. 5. Adaptiveness and Lock-free Synchronization in Parallel Stochastic Gradient Descent

    Författare :Karl Bäckström; Chalmers tekniska högskola; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; parallelism; machine learning; Stochastic gradient descent;

    Sammanfattning : The emergence of big data in recent years due to the vast societal digitalization and large-scale sensor deployment has entailed significant interest in machine learning methods to enable automatic data analytics. In a majority of the learning algorithms used in industrial as well as academic settings, the first-order iterative optimization procedure Stochastic gradient descent (SGD), is the backbone. LÄS MER