Sökning: "Pattern Recognition and Classification"

Visar resultat 1 - 5 av 38 uppsatser innehållade orden Pattern Recognition and Classification.

1. 1. Influence of Automatically Constructed Non-Equivalent Mutants on Predictions of Metamorphic Relations

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

   Författare :Johan Götborg; [2023]
   Nyckelord :Balances scorecard; Data augmentation; Machine learning; Metamorphic testing; MuJava; Mutation testing;

   Sammanfattning : Behovet av tillförlitliga, motståndskraftiga, och beständiga system är uppenbart i vårt samhälle, som i ökande grad blir allt mer beroende av mjukvarulösningar. För att uppnå tillfredsställande nivåer av säkerhet och robusthet måste alla system kontinuerligt genomgå tester. LÄS MER

3. 2. Enhancing person re-identification: leveraging DensePose for improving occlusion handling and generalization

   Master-uppsats, Lunds universitet/Matematik LTH

   Författare :Björn Elwin; Anton Fredriksson; [2023]
   Nyckelord :Mathematics and Statistics;

   Sammanfattning : In this master’s thesis we propose a DensePose-based person re-identification (re-ID) machine learning algorithm building upon previous research on this topic. DensePose, a deep neural network that performs human body part segmentation on images, forms the foundation of our approach. LÄS MER

4. 3. Modeling and Interpreting CTG Curves from Labor Using Machine Learning and Pattern Recognition

   Master-uppsats, Lunds universitet/Matematisk statistik

   Författare :Sandra Kandefelt; Sara Perklev; [2022]
   Nyckelord :machine learning; CTG; pattern recognition; labor; TOCO; FHR; Mathematics and Statistics;

   Sammanfattning : The main monitoring method during labor is cardiotocography, CTG, which measures the fetal heartbeat, FHR, as well as the uterine contractions, TOCO. The CTG is a valuable tool in assessing the fetal status and it is evaluated intermittently by clinicians during the progress of the labor. LÄS MER

5. 4. Deep Learning for Deep Water: Robust classification of ship wakes with expert in the loop

   Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

   Författare :Igor RYAZANOV; [2020-10-06]
   Nyckelord :machine learning; deep learning; pattern recognition; acoustic data analysis; shipping data; data augmentation; noise robustness; classification with data imbalance; expert-in-the-loop framework;

   Sammanfattning : This work examines the applicability of the deep learning models to pattern recognition in acoustic ocean data. The features of the dataset include noise, data scarcity and the lack of labeled samples. A deep learning model is proposed for the task of automatic wake detection. LÄS MER

7. 5. Activity Recognition Using Supervised Machine Learning and GPS Sensors

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

   Författare :Anna Gentek; [2020]
   Nyckelord :GPS; data acquisition; data processing; featureextraction; activity classification; pattern recognition; transit; public transportation;

   Sammanfattning : Human Activity Recognition has become a popular research topic among data scientists. Over the years, multiple studies regarding humans and their daily motion habits have been investigated for many different purposes. LÄS MER