Essays about: "generative network"
Showing result 1 - 5 of 152 essays containing the words generative network.
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1. Learning a Grasp Prediction Model for Forestry Applications
University essay from Umeå universitet/Institutionen för fysikAbstract : Since the advent of machine learning and machine vision methods, progress has been made in tackling the long-standing research question of autonomous grasping of arbitrary objects using robotic end-effectors. Building on these efforts, we focus on a subset of the general grasping problem concerning the automation of a forwarder. READ MORE
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2. Generative adversarial network for point cloud upsampling
University essay from Luleå tekniska universitet/Institutionen för system- och rymdteknikAbstract : Point clouds are a widely used system for the collection and application of 3D data. But most timesthe data gathered is too scarce to reliably be used in any application. READ MORE
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3. Virtual H&E Staining Using PLS Microscopy and Neural Networks
University essay from Lunds universitet/Matematik LTHAbstract : 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
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4. Despeckling Echocardiograms Using Generative Adversarial Networks
University essay from Göteborgs universitet/Institutionen för data- och informationsteknikAbstract : 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
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5. Restaurant Daily Revenue Prediction : Utilizing Synthetic Time Series Data for Improved Model Performance
University essay from Uppsala universitet/Avdelningen för beräkningsvetenskapAbstract : 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
