Essays about: "filter networks"
Showing result 1 - 5 of 93 essays containing the words filter networks.
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1. 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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2. Detection of local motion artifacts and image background in laser speckle contrast imaging
University essay from Linköpings universitet/Institutionen för medicinsk teknikAbstract : Laser speckle contrast imaging (LSCI) and its extension, multi-exposure laser speckle contrast imaging (MELSCI) are non-invasive techniques to monitor peripheral blood perfusion. One of the main drawbacks of LSCI and MELSCI in clinical use is that the techniques are sensitive to tissue movement. READ MORE
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3. Trainable Region of Interest Prediction: Hard Attention Framework for Hardware-Efficient Event-Based Computer Vision Neural Networks on Neuromorphic Processors
University essay from Lunds universitet/Institutionen för elektro- och informationsteknikAbstract : Neuromorphic processors are a promising new type of hardware for optimizing neural network computation using biologically-inspired principles. They can effectively leverage information sparsity such as in images from event-based cameras, and are well-adapted to processing event-based data in an energy-efficient fashion. READ MORE
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4. Fog detection using an artificial neural network
University essay from Lunds universitet/Matematisk statistikAbstract : This project studies a method of image-based fog detection directly from a camera without using the transmissometer. Fog can be detected using transmissometers which could be a very costly approach. This thesis presents an image-based approach for fog detection using Artificial Neural networks. READ MORE
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5. Comparison of Hebbian Learning and Backpropagation for Image Classification in Convolutional Neural Networks
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Current commonly used image recognition convolutional neural networks sharesome similarities with the human brain. However, the differences are many and the wellestablished backpropagation learning algorithm is not biologically plausible. READ MORE