Essays about: "Generative deep networks"

Showing result 1 - 5 of 106 essays containing the words Generative deep networks.

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

3. 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

4. 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

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. Technology Acceptance for AI implementations : A case study in the Defense Industry about 3D Generative Models

   University essay from KTH/Skolan för industriell teknik och management (ITM)

   Author : Michael Arenander; [2023]
   Keywords : Technology Acceptance; Artificial Intelligence; Machine Learning; 3D Generative Models; Innovation; Teknisk Acceptans; Artificiell Intelligens; Maskininlärning; 3D Generativa Modeller; Innovation;

   Abstract : Advancements in Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) has emerged into 3D object creation processes through the rise of 3D Generative Adversarial Networks (3D GAN). These networks contain 3D generative models capable of analyzing and constructing 3D objects. READ MORE