Essays about: "Oövervakat Lärande"

Showing result 1 - 5 of 17 essays containing the words Oövervakat Lärande.

1. 1. Fault Detection and Diagnosis for Automotive Camera using Unsupervised Learning

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Ziyou Li; [2023]
   Keywords : Unsupervised Learning; Autoencoders; Image Clustering; Fault Detection and Diagnosis; Morphological Operations; Hardware-in-Loop; Advanced DriverAssistance System; Oövervakad inlärning; Autoencoders; Bildklustering; Felfindning och Diagnostik; Morfologiska Operationer; Hardware-in-Loop; Avancerade Förarassistanssystem;

   Abstract : This thesis aims to investigate a fault detection and diagnosis system for automotive cameras using unsupervised learning. 1) Can a front-looking wide-angle camera image dataset be created using Hardware-in-Loop (HIL) simulations? 2) Can an Adversarial Autoencoder (AAE) based unsupervised camera fault detection and diagnosis method be crafted for SPA2 Vehicle Control Unit (VCU) using an image dataset created using Hardware-inLoop? 3) Does using AAE surpass the performance of using Variational Autoencoder (VAE) for the unsupervised automotive camera fault diagnosis model? In the field of camera fault studies, automotive cameras stand out for its complex operational context, particularly in Advanced Driver-Assistance Systems (ADAS) applications. READ MORE

3. 2. Discover patterns within train log data using unsupervised learning and network analysis

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Zehua Guo; [2022]
   Keywords : Log analysis; Natural language processing; Unsupervised learning; Clustering; Network analysis; Logganalys; Bearbetning av naturligt språk; Oövervakat lärande; Clustering; Nätverksanalys;

   Abstract : With the development of information technology in recent years, log analysis has gradually become a hot research topic. However, manual log analysis requires specialized knowledge and is a time-consuming task. Therefore, more and more researchers are searching for ways to automate log analysis. READ MORE

4. 3. Matching Sticky Notes Using Latent Representations

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Javier García San Vicent; [2022]
   Keywords : Pattern matching; Image matching; Image recognition; Representation learning; Unsupervised learning; Semisupervised learning; Siamese architecture; Deep learning; Transfer learning; Mönstermatchning; Bildmatchning; Bildigenkänning; Representationsinlärning; Oövervakat lärande; Halvövervakat lärande; Siamesisk arkitektur; Djup lärning; Överfört lärande;

   Abstract : his project addresses the issue of accurately identifying repeated images of sticky notes. Due to environmental conditions and the 3D location of the camera, different pictures taken of sticky notes may look distinct enough to be hard to determine if they belong to the same note. READ MORE

5. 4. Grouping Similar Bug Reports from Crash Dumps with Unsupervised Learning

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Sara Vestergren; [2021]
   Keywords : Unsupervised Learning; Bug Report; Duplicate Detection; Clustering; Software Crash; Oövervakad Inlärning; Felrapport; Dublett-detektering; Klustring; Mjukvarukrasch;

   Abstract : Quality software usually means high reliability, which in turn has two main components; the software should provide correctness, which means it should perform the specified task, and robustness in the sense that it should be able to manage unexpected situations. In other words, reliable systems are systems without bugs. READ MORE

6. 5. EVALUATION OF UNSUPERVISED MACHINE LEARNING MODELS FOR ANOMALY DETECTION IN TIME SERIES SENSOR DATA

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Lorenzo Bracci; Amirhossein Namazi; [2021]
   Keywords : Machine learning; Unsupervised learning; Anomaly detection; Time Series data; Maskininlärning; Oövervakat Lärande; Anomalidetektering; tidsseriedata;

   Abstract : With the advancement of the internet of things and the digitization of societies sensor recording time series data can be found in an always increasing number of places including among other proximity sensors on cars, temperature sensors in manufacturing plants and motion sensors inside smart homes. This always increasing reliability of society on these devices lead to a need for detecting unusual behaviour which could be caused by malfunctioning of the sensor or by the detection of an uncommon event. READ MORE