Essays about: "filter networks"
Showing result 1 - 5 of 117 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. 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 share some similarities with the human brain. However, the differences are many and the well established backpropagation learning algorithm is not biologically plausible. READ MORE
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3. Segment Routing Based Traffic Engineering : A QoS adaptive rerouting using segment routing approach based on IPv6 to mitigate network congestion
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : In modern networks, the increasing volume of network traffic and the diverse range of services with varying requirements necessitate the implementation of more advanced routing decisions and traffic engineering. This academic study proposes a QoS adaptive mechanism called "Sepitto", which utilizes Segment routing protocols, specifically SRv6, to address network-traffic control and congestion avoidance. READ MORE
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4. 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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5. 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