Sökning: "convolutional neural network"

Visar resultat 1 - 5 av 560 uppsatser innehållade orden convolutional neural network.

  1. 1. Establishment of a deep learning algorithm for dosimetry of radiopharmaceuticals

    Master-uppsats,

    Författare :Dennis Lipnicevic; [2022-01-13]
    Nyckelord :Medical physics; automated segmentation; dosimetry; kidney; nuclear medicine dosimetry; deep learning; convolutional neural network;

    Sammanfattning : Purpose: The aim of this study was to introduce a volumetric convolutional neural network for segmentation of the kidneys in SPECT images and to apply it in the dosimetry of radiopharmaceuticals of this organ, in order to decrease segmentation time and to standardize the segmentation of the kidneys. Method: Three networks were trained using two network architectures and a total of 216 retrospectively collected images from patients that underwent imaging procedures at Sahlgrenska University Hospital between 2009 and 2018. LÄS MER

  2. 2. Automated Digitization and Summarization of Analog Archives : Comparing summaries made by GPT-3 and a human

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Signaler och system

    Författare :Maja Linderholm; [2022]
    Nyckelord :;

    Sammanfattning : This thesis aimed to create a tool that could assist climate researchers in their fieldwork. Through dialog with researchers at Stockholms University a need and interest for automated digitization and summarization of their handwritten notes could be identified. LÄS MER

  3. 3. Virtual Staining of Blood Cells using Point Light Source Illumination and Deep Learning

    Master-uppsats, Lunds universitet/Matematik LTH

    Författare :Joel Wulff; [2022]
    Nyckelord :Deep learning; virtual staining; blood; cells; GANs; Generative adversarial networks; CNNs; convolutional neural networks; ESRGAN; Unet; digital microscopy; Mathematics and Statistics;

    Sammanfattning : Blood tests are an important part of modern medicine, and are essentially always stained using chemical colorization methods before analysis by computational or manual methods. The staining process allows different parts of blood cells to be discerned that would be unnoticeable in unstained blood. LÄS MER

  4. 4. Deep neural networks for food waste analysis and classification : Subtraction-based methods for the case of data scarcity

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Signaler och system

    Författare :David Brunell; [2022]
    Nyckelord :Siamese network; convolutional neural network;

    Sammanfattning : Machine learning generally requires large amounts of data, however data is often limited. On the whole the amount of data needed grows with the complexity of the problem to be solved. Utilising transfer learning, data augmentation and problem reduction, acceptable performance can be achieved with limited data for a multitude of tasks. LÄS MER

  5. 5. Non-Bayesian Out-of-Distribution Detection Applied to CNN Architectures for Human Activity Recognition

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

    Författare :Serghei Socolovschi; [2022]
    Nyckelord :Human Activity Recognition; Deep Learning; Time Series; Uncertainty Estimation; Outofdistribution Detection; Convolutional Neural Network; Human Activity Recognition; Deep Learning; Tidsserie; Uppskattning av Osäkerheten; Outofdistribution Detection; Convolutional Neural Network;

    Sammanfattning : Human Activity Recognition (HAR) field studies the application of artificial intelligence methods for the identification of activities performed by people. Many applications of HAR in healthcare and sports require the safety-critical performance of the predictive models. LÄS MER