Box plots of infection and detection time differences. حسب Soler Gabriela Bayolo (21011810)

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Interactions between individuals over three days. حسب Soler Gabriela Bayolo (21011810)

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Effect of <i>η</i> and on epidemic spread. حسب Soler Gabriela Bayolo (21011810)

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Effect of the quarantine adoption fraction <i>q</i> on epidemic spread. حسب Soler Gabriela Bayolo (21011810)

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Effect of the estimators (blue), (orange), and the real time of infection (green). حسب Soler Gabriela Bayolo (21011810)

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Comparison of infection time estimators. حسب Soler Gabriela Bayolo (21011810)

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Effect of the transmission probability function on epidemic spread. حسب Soler Gabriela Bayolo (21011810)

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Effect of <i>γ</i> on epidemic spread. حسب Soler Gabriela Bayolo (21011810)

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Effect of super-spreaders on ranking methods. حسب Soler Gabriela Bayolo (21011810)

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Effect of sensitivity and specificity on epidemic spread. حسب Soler Gabriela Bayolo (21011810)

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Effect of and on epidemic spread. حسب Soler Gabriela Bayolo (21011810)

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Solid-State Nanopore Sensors: Analyte Quantification by Event Frequency Analysis at High Voltages حسب Julia Järlebark (14601273)

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A New Control Approach for a Multi-Controlled Wheelchair Utilizing Deep Learning Framework and Raspberry Pi حسب Sudipta Chatterjee (536333)

"…The proposed wheelchair can navigate in any direction using object detection techniques powered by OpenCV. Employing a deep learning algorithm, it performs real-time object detection and tracks its current position in various environmental conditions. …"

Data Sheet 1_Functional partitioning through competitive learning.pdf حسب Marius Tacke (22563344)

"…We propose a novel partitioning algorithm that utilizes competition between models to detect and separate these functional patterns. …"

Table 4_The potential of short-wave infrared hyperspectral imaging and deep learning for dietary assessment: a prototype on predicting closed sandwiches fillings.docx حسب Esther Kok (716077)

"…</p>Methods<p>Individual spectra were selected from 24 hyperspectral images of assembled closed sandwiches, measured in a spectral range of 1116.14 nm to 1670.62 nm over 108 bands, pre-processed with Standard Normal Variate filtering, derivatives, and subsampling, and fed into multiple algorithms, among which PLS-DA, multiple classifiers, and a simple neural network.…"

Table 3_The potential of short-wave infrared hyperspectral imaging and deep learning for dietary assessment: a prototype on predicting closed sandwiches fillings.docx حسب Esther Kok (716077)

"…</p>Methods<p>Individual spectra were selected from 24 hyperspectral images of assembled closed sandwiches, measured in a spectral range of 1116.14 nm to 1670.62 nm over 108 bands, pre-processed with Standard Normal Variate filtering, derivatives, and subsampling, and fed into multiple algorithms, among which PLS-DA, multiple classifiers, and a simple neural network.…"

Table 2_The potential of short-wave infrared hyperspectral imaging and deep learning for dietary assessment: a prototype on predicting closed sandwiches fillings.docx حسب Esther Kok (716077)

"…</p>Methods<p>Individual spectra were selected from 24 hyperspectral images of assembled closed sandwiches, measured in a spectral range of 1116.14 nm to 1670.62 nm over 108 bands, pre-processed with Standard Normal Variate filtering, derivatives, and subsampling, and fed into multiple algorithms, among which PLS-DA, multiple classifiers, and a simple neural network.…"

Table 1_The potential of short-wave infrared hyperspectral imaging and deep learning for dietary assessment: a prototype on predicting closed sandwiches fillings.docx حسب Esther Kok (716077)

"…</p>Methods<p>Individual spectra were selected from 24 hyperspectral images of assembled closed sandwiches, measured in a spectral range of 1116.14 nm to 1670.62 nm over 108 bands, pre-processed with Standard Normal Variate filtering, derivatives, and subsampling, and fed into multiple algorithms, among which PLS-DA, multiple classifiers, and a simple neural network.…"