Essays about: "Deep neural networks"
Showing result 21 - 25 of 862 essays containing the words Deep neural networks.
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21. Modelling Proxy Credit Cruves Using Recurrent Neural Networks
University essay from KTH/Matematisk statistikAbstract : Since the global financial crisis of 2008, regulatory bodies worldwide have implementedincreasingly stringent requirements for measuring and pricing default risk in financialderivatives. Counterparty Credit Risk (CCR) serves as the measure for default risk infinancial derivatives, and Credit Valuation Adjustment (CVA) is the pricing method used toincorporate this default risk into derivatives prices. READ MORE
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22. Exploration of using Twitter data to predict Swedish political opinion polls with neural networks
University essay from Lunds universitet/Matematisk statistikAbstract : This thesis aims to explore the possibility of using deep learning techniques to mine opinions on Twitter, with the objective to predict the political opinion distribution in Sweden. Different methods of gathering and annotating training data are evaluated to achieve accurate and reliable predictions. READ MORE
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23. Evaluating the Viability of Synthetic Pre-training Data for Face Recognition Using a CNN-Based Multiclass Classifier
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Today, face recognition is becoming increasingly accurate and faster with deep learning methods such as convolutional neural networks (CNNs), and is now widely used in areas such as security and entertainment. Typically, these CNNs are trained using real-face datasets like CASIA-WebFace, which was put together using web-crawling of IMDB. READ MORE
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24. Exploration and Evaluation of RNN Models on Low-Resource Embedded Devices for Human Activity Recognition
University essay from KTH/Mekatronik och inbyggda styrsystemAbstract : Human activity data is typically represented as time series data, and RNNs, often with LSTM cells, are commonly used for recognition in this field. However, RNNs and LSTM-RNNs are often too resource-intensive for real-time applications on resource constrained devices, making them unsuitable. READ MORE
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25. Improved U-Net architecture for Crack Detection in Sand Moulds
University essay from Högskolan i Gävle/DatavetenskapAbstract : The detection of cracks in sand moulds has long been a challenge for both safety and maintenance purposes. Traditional image processing techniques have been employed to identify and quantify these defects but have often proven to be inefficient, labour-intensive, and time-consuming. READ MORE
