Quantizing linear computations over the reals is a common practice in many distributed systems, with applications in efficient, private, or robust machine learning algorithms. Recent work studied the access parameter ...
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Flight data collected from an Automatic Dependent Surveillance-Broadcast (ADS-B) can be used to make inferences about aircraft characteristics. This work uses all flight phases to identify an aircraft's Wake Turbu...
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This paper presents a novel two-stage approach to enhance the quality and privacy of X-ray medical images. The first stage leverages generative adversarial networks (GANs) for effective denoising, eliminating noise an...
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The bandwidth and latency requirements of modern datacenter applications have led researchers to propose various topology designs using static, dynamic demand-oblivious (rotor), and/or dynamic demand-aware switches. H...
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Control devices such as inverters and generator controllers are critical for the stable operation of the power grid, especially for power stability control and power dispatch. However, the Electromagnetic Pulse (EMP) ...
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The gradual decommissioning of fossil fuel-driven power plants, that traditionally provide most operational flexibility in power systems, has led to more frequent grid stability issues. To compensate for the lack of f...
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Background Determining how an image is visually appealing is a complicated and subjective task. This motivates the use of a machine-learning model to evaluate image aesthetics automatically by matching the aesthetics ...
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Background Determining how an image is visually appealing is a complicated and subjective task. This motivates the use of a machine-learning model to evaluate image aesthetics automatically by matching the aesthetics of the general public. Although deep learning methods have successfully learned good visual features from images,correctly assessing the aesthetic quality of an image remains a challenge for deep learning. Methods To address this, we propose a novel multiview convolutional neural network to assess image aesthetics assessment through color composition and space formation(IAACS). Specifically, from different views of an image––including its key color components and their contributions, the image space formation, and the image itself––our network extracts the corresponding features through our proposed feature extraction module(FET) and the Image Net weight-based classification model. Result By fusing the extracted features, our network produces an accurate prediction score distribution for image aesthetics. The experimental results show that we have achieved superior performance.
This paper investigates optimization of parameters to enhance performance of a microwave resonant cavity transducer for high temperature fluid flow sensing in advanced reactors. The cylindrical microwave cavity flowme...
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Linear real-valued computations over distributed datasets are common in many applications, most notably as part of machine learning inference. In particular, linear computations which are quantized, i.e., where the co...
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Modeling bias - the difference between the test accuracy obtained by a reference network prototype and a simulated model of that prototype - is explored in the context of hafnia-based ferroelectric field effect transi...
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