Essays about: "Generative adversarial networks"

Showing result 1 - 5 of 138 essays containing the words Generative adversarial networks.

1. 1. 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

3. 2. 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

4. 3. 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

5. 4. Domain Adaptation for Multi-Contrast Image Segmentation in Cardiac Magnetic Resonance Imaging

   University essay from KTH/Skolan för kemi, bioteknologi och hälsa (CBH)

   Author : Thomas Proudhon; [2023]
   Keywords : Cardiac Magnetic Resonance Imaging; Deep Learning; Domain Adaptation; Unsupervised Segmentation; Image-to-image Translation;

   Abstract : Accurate segmentation of the ventricles and myocardium on Cardiac Magnetic Resonance (CMR) images is crucial to assess the functioning of the heart or to diagnose patients suffering from myocardial infarction. However, the domain shift existing between the multiple sequences of CMR data prevents a deep learning model trained on a specific contrast to be used on a different sequence. READ MORE

6. 5. Using Generative Adversarial Networks for H&E-to-HER2 Stain Translation in Digital Pathology Images

   University essay from Linköpings universitet/Institutionen för medicinsk teknik

   Author : William Tirmén; [2023]
   Keywords : Machine learning; Artificial intelligence; Digital pathology; Image processing; Generative adversarial networks; Image-to-image translation;

   Abstract : In digital pathology, hematoxylin & eosin (H&E) is a routine stain which is performed on most clinical cases and it often provides clinicians with sufficient information for diagnosis. However, when making decisions on how to guide breast cancer treatment, immunohistochemical staining of human epidermal growth factor 2 (HER2 staining) is also needed. READ MORE