Essays about: "residual neural network"
Showing result 1 - 5 of 30 essays containing the words residual neural network.
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1. Unsupervised Online Anomaly Detection in Multivariate Time-Series
University essay from Uppsala universitet/DatorteknikAbstract : This research aims to identify a method for unsupervised online anomaly detection in multivariate time series in dynamic systems in general and on the case study of Devwards IoT-system in particular. A requirement of the solution is its explainability, online learning and low computational expense. READ MORE
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2. Room Impulse Response Interpolation
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : In Virtual Reality (VR) systems, the incorporation of acoustics allows for the generation of audio-visual stimuli, facilitating applications in engineering, architecture, and design. The goal of virtual acoustics is to create a realistic sound field in continuous space. READ MORE
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3. Straight to the Heart : Classification of Multi-Channel ECG-signals using MiniROCKET
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Machine Learning (ML) has revolutionized various domains, with biomedicine standing out as a major beneficiary. In the realm of biomedicine, Convolutional Neural Networks (CNNs) have notably played a pivotal role since their inception, particularly in applications such as time-series classification. READ MORE
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4. Deep learning for temporal super-resolution of 4D Flow MRI
University essay from KTH/Matematik (Avd.)Abstract : The accurate assessment of hemodynamics and its parameters play an important role when diagnosing cardiovascular diseases. In this context, 4D Flow Magnetic Resonance Imaging (4D Flow MRI) is a non-invasive measurement technique that facilitates hemodynamic parameter assessment as well as quantitative and qualitative analysis of three-directional flow over time. READ MORE
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5. Probabilistic Forecasting through Reformer Conditioned Normalizing Flows
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Forecasts are essential for human decision-making in several fields, such as weather forecasts, retail prices, or stock predictions. Recently the Transformer neural network, commonly used for sequence-to-sequence tasks, has shown great potential in achieving state-of-the-art forecasting results when combined with density estimations models such as Autoregressive Flows. READ MORE