Sökning: "oövervakade modeller"

Visar resultat 1 - 5 av 13 uppsatser innehållade orden oövervakade modeller.

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

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

   Författare :Ziyou Li; [2023]
   Nyckelord :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;

   Sammanfattning : 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. LÄS MER

3. 2. Evaluation of the performance of machine learning techniques for email classification

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

   Författare :Isabella Tapper; [2022]
   Nyckelord :Natural Language Processing; Text Representations; Email Classification; Text Classification; Behandling Av Naturliga Språk; Text Representation; epost-klassificering; Textklassificering;

   Sammanfattning : Manual categorization of a mail inbox can often become time-consuming. Therefore many attempts have been made to use machine learning for this task. One essential Natural Language Processing (NLP) task is text classification, which is a big challenge since an NLP engine is not a native speaker of any human language. LÄS MER

4. 3. An unsupervised method for Graph Representation Learning

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

   Författare :Yi Ren; [2022]
   Nyckelord :Graph Representation Learning; unsupervised learning; machine learning;

   Sammanfattning : Internet services, such as online shopping and chat apps, have been spreading significantly in recent years, generating substantial amounts of data. These data are precious for machine learning and consist of connections between different entities, such as users and items. LÄS MER

5. 4. A deep learning based anomaly detection pipeline for battery fleets

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

   Författare :Nabakumar Singh Khongbantabam; [2021]
   Nyckelord :Forklift batteries; Battery sensors; Data pipeline; Predictive maintenance; Anomaly detection; Deep learning; Battery failure prediction; Time-series; Variational autoencoder; Long short-term memory; LSTM; Gated recurrent unit; GRU; Isolation nearest neighbor; iNNE; Isolation forest; iForest; kth nearest neighbor; kNN.; Gaffeltruckbatterier; Batterisensorer; Datapipeline; Prediktivt underhåll; Avvikelsedetektering; Deep learning; Batterifelsprediktion; Tidsserier; Variationsautokodare; Långt korttidsminne; LSTM; Gated recurrent unit; GRU; Isolation närmaste granne; iNNE; Isolation skog; iForest; kth närmaste granne; kNN.;

   Sammanfattning : This thesis proposes a deep learning anomaly detection pipeline to detect possible anomalies during the operation of a fleet of batteries and presents its development and evaluation. The pipeline employs sensors that connect to each battery in the fleet to remotely collect real-time measurements of their operating characteristics, such as voltage, current, and temperature. LÄS MER

7. 5. Textbrytning av mäklartexter och slutpris : Med BERT, OLS och Elman regressionsnätverk

   M1-uppsats, KTH/Hälsoinformatik och logistik

   Författare :Emil Fjellström; Johan Challita; [2021]
   Nyckelord :BERT; OLS; Elman regression; machine learning; supervised models; unsupervised models; broker texts; attributes; BERT; OLS; Elman regression; maskininlärning; övervakade modeller; oövervakade modeller; mäklartexter; attribut;

   Sammanfattning : Att estimera slutpriset av en bostadsförsäljning är en komplex uppgift där mäklartexter som beskriver bostäder är en vital del av försäljningen. Denna rapport undersöker om det går att använda mäklartexter för att generera mer träffsäkra estimeringar med maskininlärningsmodeller. LÄS MER