Essays about: "Embedding Network"
Showing result 1 - 5 of 73 essays containing the words Embedding Network.
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1. Planet-NeRF : Neural Radiance Fields for 3D Reconstruction on Satellite Imagery in Season Changing Environments
University essay from Linköpings universitet/DatorseendeAbstract : This thesis investigates the seasonal predictive capabilities of Neural Radiance Fields (NeRF) applied to satellite images. Focusing on the utilization of satellite data, the study explores how Sat-NeRF, a novel approach in computer vision, per- forms in predicting seasonal variations across different months. READ MORE
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2. Deep Learning Based Sentiment Analysis
University essay from Blekinge Tekniska Högskola/Institutionen för datavetenskapAbstract : Background: Text data includes things like customer reviews and complaints,tweets from social media platforms. When analyzing text-based data, the SentimentModel is used. Understanding news headlines, blogs, the stock market, politicaldebates, and film reviews some of the areas where sentiment analysis is used. READ MORE
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3. Identification of Fibers in Micro-CT Images of Paperboard Using Deep Learning
University essay from Lunds universitet/Hållfasthetslära; Lunds universitet/Institutionen för byggvetenskaperAbstract : This master thesis project explores the possibility of using deep learning to segment individual fibers in three-dimensional tomography images of paperboard fiber networks. We test a method which has previously been used to segment fibers in images of glass fiber reinforced polymers. READ MORE
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4. Sustainable Recipe Recommendation System: Evaluating the Performance of GPT Embeddings versus state-of-the-art systems
University essay from Blekinge Tekniska Högskola/Institutionen för datavetenskapAbstract : Background: The demand for a sustainable lifestyle is increasing due to the need to tackle rapid climate change. One-third of carbon emissions come from the food industry; reducing emissions from this industry is crucial when fighting climate change. READ MORE
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5. RNN-based Graph Neural Network for Credit Load Application leveraging Rejected Customer Cases
University essay from Högskolan i Halmstad/Akademin för informationsteknologiAbstract : Machine learning plays a vital role in preventing financial losses within the banking industry, and still, a lot of state of the art and industry-standard approaches within the field neglect rejected customer information and the potential information that they hold to detect similar risk behavior.This thesis explores the possibility of including this information during training and utilizing transactional history through an LSTM to improve the detection of defaults. READ MORE