image compression plays a key role in contemporary digital environments given the escalating influx of visual data on the internet. In this study, the K-means clustering algorithm is adopted for Ultra High Definition ...
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The reliable operation of power grids is increasingly dependent on advanced fault diagnosis systems capable of identifying both known and emerging fault types. Traditional and many contemporary methods often struggle ...
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The early recognition of retinal disorders such as cataracts, glaucoma, and retinal problems is highly dependent on high-resolution retinal imaging, which is a complex issue because of poor image quality and the lack ...
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A clandestine intelligence tactic emerged, involving the concealment of data within images reduced to a minuscule size, imperceptible to the human eye. In the modern era, characterized by the proliferation of internet...
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This work proposes an interpretable classifier for automatic Covid-19 classification using chest X-ray images. It is based on a deep learning model, in particular, a triplet network, devoted to finding an effective im...
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ISBN:
(纸本)9781665464956
This work proposes an interpretable classifier for automatic Covid-19 classification using chest X-ray images. It is based on a deep learning model, in particular, a triplet network, devoted to finding an effective image embedding. Such embedding is a non-linear projection of the images into a space of reduced dimension, where homogeneity and separation of the classes measured by a predefined metric are improved. A KNearest Neighbor classifier is the interpretable model used for the final classification. Results on public datasets show that the proposed methodology can reach comparable results with state of the art in terms of accuracy, with the advantage of providing interpretability to the classification, a characteristic which can be very useful in the medical domain, e.g. in a decision support system.
The prevalence of sensors and sensor networks has resulted in the internet of Things (IoT), transforming modern lifestyles. However, resource-constrained IoT edge devices require inventive sensing, computing, and wire...
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ISBN:
(纸本)9798350387186;9798350387179
The prevalence of sensors and sensor networks has resulted in the internet of Things (IoT), transforming modern lifestyles. However, resource-constrained IoT edge devices require inventive sensing, computing, and wireless telemetry strategies to support the massive number of devices in an IoT network. Traditional telemetry and data encoding schemes for short-range sensor networks are limited by network bandwidth, data processing capability, and power constraints imposed by the battery energy density. To mitigate these challenges, an energy-efficient architecture is presented for analog orthogonal pulse (AOP) generation and AOP-based data encoding for high-density spectrum-efficient wireless telemetry. Unlike conventional digital pulse-based encoding, higher-order analog orthogonal pulses are used for spectrum-efficient data encoding. The orthogonal pulse generator contained a reduced number of functional blocks for energy efficiency. The MATLAB-Simulink package is used to design and simulate the proposed encoding architecture and, finally, embedded into a microcontroller unit. Test results show the successful generation of analog orthogonal pulses and pulse-basedsignal encoding.
The Electrocardiogram (ECG) signal is an important tool for cardiovascular diseases analysis. However, still today acquisition devices produce noisy signals that degrades the quality of information by corrupting impor...
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ISBN:
(纸本)9781665464956
The Electrocardiogram (ECG) signal is an important tool for cardiovascular diseases analysis. However, still today acquisition devices produce noisy signals that degrades the quality of information by corrupting important features. To improve the quality of the acquired data a filtering process is mandatory. Moreover, a real-time filtering of ECGs, in order to obtain a diagnosis as quickly as possible is a very interesting challenge. In this paper, we consider as denoising filter, the Savitzky-Golay method and we propose a parallel algorithm implementing it. The procedure exploits the computational power of Graphics Processing Units (GPUs). Results in terms of performance and quality are provided.
Recent advance in computer network and camera technology, the volume of face image data on the internet is expanding rapidly. However, these images often suffer from hole-like missing or occlusions that can compromise...
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Scanning electron microscopy (SEM) has emerged as a pivotal tool in scientific research and engineering, offering unparalleled insights into the micro- and nano-scale world. However, traditional SEM systems often enta...
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Ground penetrating radar (GPR) represents an established non-destructive detection technology. Enhancing resolution of low-frequency GPR data of a broad detection enables acquisition of high-quality GPR images, which ...
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