Sökning: "adaptive thresholding"

Visar resultat 1 - 5 av 7 uppsatser innehållade orden adaptive thresholding.

1. 1. Anomaly Detection in the EtherCAT Network of a Power Station : Improving a Graph Convolutional Neural Network Framework

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

   Författare :Niklas Barth; [2023]
   Nyckelord :Unsupervised Learning; Multivariate Time Series; Graph Convolutional Neural Networks; Anomaly Detection; Industrial Control System; EtherCAT; Power Station; Electricity Grid;

   Sammanfattning : In this thesis, an anomaly detection framework is assessed and fine-tuned to detect and explain anomalies in a power station, where EtherCAT, an Industrial Control System, is employed for monitoring. The chosen framework is based on a previously published Graph Neural Network (GNN) model, utilizing attention mechanisms to capture complex relationships between diverse measurements within the EtherCAT system. LÄS MER

3. 2. Automatic Detection of Structural Deformations in Batteries from Imaging data using Machine Learning : Exploring the potential of different approaches for efficient structural deformation detection

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

   Författare :Maira Khan; [2023]
   Nyckelord :CT scan; electrode peaks; jelly roll; keypoints; structural deformation; traditional computer vision; deep neural network; CT-skanning; elektrodtoppar; gelérulle; nyckelpunkter; strukturell deformation; Traditionellt datorseende; djupt neuralt nätverk;

   Sammanfattning : The increasing occurrence of structural deformations in the electrodes of the jelly roll has raised quality concerns during battery manufacturing, emphasizing the need to detect them automatically with the advanced techniques. This thesis aims to explore and provide two models based on traditional computer vision (CV) and deep neural network (DNN) techniques using computed tomography (CT) scan images of jelly rolls to ensure that the product is of high quality. LÄS MER

4. 3. A Phantom Based Comparison of Image Segmentation Algorithms for Adaptive Functional Volume Determination of the Thyroid Gland using SPECT

   Uppsats för yrkesexamina på avancerad nivå, Stockholms universitet/Fysikum

   Författare :Henrik Berg; [2021]
   Nyckelord :Hyperthyroidism; Nuclear Medicine; SPECT; Functional Volume; Phantom Study; Adaptive Image Segmentation; Thresholding; Region Growing;

   Sammanfattning : Background One of the most used treatments for hyperthyroidism, is therapy with radioactive iodine (131I), which is accumulated in the thyroid gland. To determine the activity of 131I to be administered for a certain absorbed dose, the volume of the gland is of great importance but the historically used methods for estimating the functional volume of the gland are based on large approximations. LÄS MER

5. 4. Differences in tumor volume for treated glioblastoma patients examined with 18F-fluorothymidine PET and contrast-enhanced MRI

   Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för fysik

   Författare :Karolina Hedman; [2020]
   Nyckelord :PET MRI; positron emission tomography; magnetic resonance imaging; brain tumor; glioblastoma; image segmentation; adaptive thresholding; feature extraction; radiotracer; gadolinium; image processing; image analysis;

   Sammanfattning : Background: Glioblastoma (GBM) is the most common and malignant primary brain tumor. It is a rapidly progressing tumor that infiltrates the adjacent healthy brain tissue and is difficult to treat. Despite modern treatment including surgical resection followed by radiochemotherapy and adjuvant chemotherapy, the outcome remains poor. LÄS MER

7. 5. Classification of skin pixels in images : Using feature recognition and threshold segmentation

   Kandidat-uppsats, Umeå universitet/Institutionen för datavetenskap

   Författare :Emil Samuelsson; [2018]
   Nyckelord :;

   Sammanfattning : The purpose of this report is to investigate and answer the research question: How can current skin segmentation thresholding methods be improved in terms of precision, accuracy, and efficiency by using feature recognition, pre- and post-processing? In this work, a novel algorithm is presented for classification of skin pixels in images. Different pre-processing methods were evaluated to improve the overall performance of the algorithm. LÄS MER