Sökning: "ensemble"

Visar resultat 6 - 10 av 547 uppsatser innehållade ordet ensemble.

1. 6. Mutual Enhancement of Environment Recognition and Semantic Segmentation in Indoor Environment

   Master-uppsats,

   Författare :Venkata Vamsi Challa; [2024]
   Nyckelord :Semantic Segmentation; Scene Classification; Environment Recognition; Machine Learning; Deep Learning; Image Classification; Vision Transformers; SAM Segment Anything Model ; Image Segmentation; Contour-aware semantic segmentation;

   Sammanfattning : Background:The dynamic field of computer vision and artificial intelligence has continually evolved, pushing the boundaries in areas like semantic segmentation andenvironmental recognition, pivotal for indoor scene analysis. This research investigates the integration of these two technologies, examining their synergy and implicayions for enhancing indoor scene understanding. LÄS MER

3. 7. Context-aware security testing of Android applications : Detecting exploitable vulnerabilities through Android model-based security testing

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

   Författare :Ivan Baheux; [2023]
   Nyckelord :Android Application Security; Vulnerability Detection; Context-Awareness; Model-Based Security Testing; Domain Specific Language; Sécurité des Applications Android; Détection de Vulnérabilités; Sensibilité au Contexte; Tests de Sécurité Basés sur les Modèles; Langage Dédiés; Android-applikationssäkerhet; Upptäckt av sårbarheter; Kontextmedvetenhet; Modellbaserad säkerhetstestning; Domänspecifikt språk;

   Sammanfattning : This master’s thesis explores ways to uncover and exploit vulnerabilities in Android applications by introducing a novel approach to security testing. The research question focuses on discovering an effective method for detecting vulnerabilities related to the context of an application. LÄS MER

4. 8. MetaStackVis: Visually-Assisted Performance Evaluation of Metamodels in Stacking Ensemble Learning

   Kandidat-uppsats, Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)

   Författare :Ilya Ploshchik; [2023]
   Nyckelord :Visualization; interaction; metamodels; validation metrics; predicted probabilities; stacking; stacked generalization; ensemble learning; machine learning;

   Sammanfattning : Stacking, also known as stacked generalization, is a method of ensemble learning where multiple base models are trained on the same dataset, and their predictions are used as input for one or more metamodels in an extra layer. This technique can lead to improved performance compared to single layer ensembles, but often requires a time-consuming trial-and-error process. LÄS MER

5. 9. Stock market analysis with a Markovian approach: Properties and prediction of OMXS30

   Kandidat-uppsats, KTH/Matematisk statistik

   Författare :Max Aronsson; Anna Folkesson; [2023]
   Nyckelord :Markov chain; OMXS30; Markov chain properties; voting ensemble model; markovkedja; OMXS30; egenskaper hos markovkedjor; ensemble-modell;

   Sammanfattning : This paper investigates how Markov chain modelling can be applied to the Swedish stock index OMXS30. The investigation is two-fold. Firstly, a Markov chain is based on index data from recent years, where properties such as transition matrix, stationary distribution and hitting time are studied. LÄS MER

7. 10. Unsupervised Online Anomaly Detection in Multivariate Time-Series

   Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Datorteknik

   Författare :Ludvig Segerholm; [2023]
   Nyckelord :unsupervised; online; anomaly detection; explainable ai; machine learning; mahalanobis distance;

   Sammanfattning : This research aims to identify a method for unsupervised online anomaly detection in multivariate time series in dynamic systems in general and on the case study of Devwards IoT-system in particular. A requirement of the solution is its explainability, online learning and low computational expense. LÄS MER