Sökning: "övervakad inlärning"

Visar resultat 1 - 5 av 6 avhandlingar innehållade orden övervakad inlärning.

1. 1. Visual Analytics for Explainable and Trustworthy Machine Learning

   Författare :Angelos Chatzimparmpas; Andreas Kerren; Rafael M. Martins; Ilir Jusufi; Alex Endert; Linnéuniversitetet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; visualization; interaction; visual analytics; explainable machine learning; XAI; trustworthy machine learning; ensemble learning; dimensionality reduction; supervised learning; unsupervised learning; ML; AI; tabular data; visualisering; interaktion; visuell analys; förklarlig maskininlärning; XAI; pålitlig maskininlärning; ensembleinlärning; dimensionesreducering; övervakad inlärning; oövervakad inlärning; ML; AI; tabelldata; Computer Science; Datavetenskap; Informations- och programvisualisering; Information and software visualization;

   Sammanfattning : The deployment of artificial intelligence solutions and machine learning research has exploded in popularity in recent years, with numerous types of models proposed to interpret and predict patterns and trends in data from diverse disciplines. However, as the complexity of these models grows, it becomes increasingly difficult for users to evaluate and rely on the model results, since their inner workings are mostly hidden in black boxes, which are difficult to trust in critical decision-making scenarios. LÄS MER

3. 2. On the Metric-based Approach to Supervised Concept Learning

   Författare :Niklas Lavesson; Sweden Karlskrona Blekinge Institute of Technology School of Engineering Department of Systems and Software Engineering; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; classifier evaluation; supervised learning; metric; criteria;

   Sammanfattning : A classifier is a piece of software that is able to categorize objects for which the class is unknown. The task of automatically generating classifiers by generalizing from examples is an important problem in many practical applications. This problem is often referred to as supervised concept learning, and has been shown to be relevant in e.g. LÄS MER

4. 3. Parameter Estimation : Towards Data-Driven and Privacy Preserving Approaches

   Författare :Braghadeesh Lakshminarayanan; Cristian R. Rojas; Simone Garatti; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Parameter estimation; System identification;

   Sammanfattning : Parameter estimation is a pivotal task across various domains such as system identification, statistics, and machine learning. The literature presents numerous estimation procedures, many of which are backed by well-studied asymptotic properties. LÄS MER

5. 4. Statistical methods in medical image estimation and sparse signal recovery

   Författare :Fekadu Lemessa Bayisa; Jun Yu; Ottmar Cronie; Henning Omre; Umeå universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; Computed tomography; magnetic resonance imaging; Gaussian mixture model; skew-Gaussian mixture model; hidden Markov random field; hidden Markov model; supervised statistical learning; synthetic CT images; pseudo-CT images; spike and slab prior; adaptive algorithm;

   Sammanfattning : This thesis presents work on methods for the estimation of computed tomography (CT) images from magnetic resonance (MR) images for a number of diagnostic and therapeutic workflows. The study also demonstrates sparse signal recovery method, which is an intermediate method for magnetic resonance image reconstruction. LÄS MER

7. 5. Multi-Modal Deep Learning with Sentinel-1 and Sentinel-2 Data for Urban Mapping and Change Detection

   Författare :Sebastian Hafner; Yifang Ban; Paolo Gamba; KTH; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Geoinformatics; Geoinformatik;

   Sammanfattning : Driven by the rapid growth in population, urbanization is progressing at an unprecedented rate in many places around the world. Earth observation has become an invaluable tool to monitor urbanization on a global scale by either mapping the extent of cities or detecting newly constructed urban areas within and around cities. LÄS MER