Advanced search

Showing result 1 - 5 of 143 essays matching the above criteria.

  1. 1. Virtual H&E Staining Using PLS Microscopy and Neural Networks

    University essay from Lunds universitet/Matematik LTH

    Author : Sally Vizins; Hanna Råhnängen; [2024]
    Keywords : Deep learning; Virtual staining; Skin tissue; Hematoxylin Eosin; H E; Pathology; Carcinoma; Point light source illumination; Neural Networks; GANs; Generative adversarial networks; CNNs; Convolutional neural networks; Relativistic generative adversarial network; Unet; Digital microscopy; Attention-Unet; Dense-Unet; Mathematics and Statistics;

    Abstract : Histopathological examination, crucial in diagnosing diseases such as cancer, traditionally relies on time- and resource-consuming, poorly standardized chemical staining for tissue visualization. This thesis presents a novel digital alternative using generative neural networks and a point light source (PLS) microscope to transform unstained skin tissue images into their stained counterparts. READ MORE

  2. 2. Despeckling Echocardiograms Using Generative Adversarial Networks

    University essay from Göteborgs universitet/Institutionen för data- och informationsteknik

    Author : Falk DIppel; [2023-10-23]
    Keywords : Generative adversarial network; deep learning; echocardiography; speckle noise; denoising; segmentation;

    Abstract : Previous research had shown that generative adversarial networks (GANs) are capable of despeckling echocardiograms (echos) through image-to-image translation in real-time once trained. However, only limited information regarding the quality of denoised echos and explainability of useful GAN components is provided. READ MORE

  3. 3. Restaurant Daily Revenue Prediction : Utilizing Synthetic Time Series Data for Improved Model Performance

    University essay from Uppsala universitet/Avdelningen för beräkningsvetenskap

    Author : Stella Jarlöv; Anton Svensson Dahl; [2023]
    Keywords : demand forecasting; data augmentation; time series data; machine learning; restaurant industry; generative adversarial networks; TimeGAN; XGBoost;

    Abstract : This study aims to enhance the accuracy of a demand forecasting model, XGBoost, by incorporating synthetic multivariate restaurant time series data during the training process. The research addresses the limited availability of training data by generating synthetic data using TimeGAN, a generative adversarial deep neural network tailored for time series data. READ MORE

  4. 4. Using Synthetic Data to ModelMobile User Interface Interactions

    University essay from Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)

    Author : Laoa Jalal; [2023]
    Keywords : Time Series Data; Generative Adversarial Networks; Synthetic Data Generator; Usability Testing; Machine Learning;

    Abstract : Usability testing within User Interface (UI) is a central part of assuring high-quality UIdesign that provides good user-experiences across multiple user-groups. The processof usability testing often times requires extensive collection of user feedback, preferablyacross multiple user groups, to ensure an unbiased observation of the potential designflaws within the UI design. READ MORE

  5. 5. Exploring GANs to generate attack-variations in IoT networks

    University essay from Uppsala universitet/Institutionen för informationsteknologi

    Author : Gustaf Bennmarker; [2023]
    Keywords : ;

    Abstract : Data driven IDS development requires a vast amount of data to be effective against future attacks and a big problem is the lack of available data. This thesis explores the use of GANs (Generative adversarial networks) in generating attack data that can be used as apart of a training set for an IDS to improve the robustness against adversarial attacks. READ MORE