Image Processing
The following datasets contains the results of an image analsyis conducted on 48 samples. The samples were prepared to study the effect of the printing strategy on the deposition on an Ag-nanoparticle ink on Kapton. The raster superposition, the splat superposition, the number of layers, and deposition strategy were used as process factors. The area of the printed pattern has been used as yield.
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The 3DLSC-COVID datset includes a total of 1,805 3D chest CT scans with more than 570,000 CT slices were collected from 2 standard CT scanners of Liyuan Hospital, i.e., UIH uCT 510 and GE Optima CT600. Among all CT scans, there were 794 positive cases of COVID-19, which were further confirmed by clinical symptoms and RT-PCR from January 16 to April 16, 2020.
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YonseiStressImageDatabase is a database built for image-based stress recognition research. We designed an experimental scenario consisting of steps that cause or do not cause stress; Native Language Script Reading, Native Language Interview, Non-native Language Script Reading, Non-native Language Interview. And during the experiment, the subjects were photographed with Kinect v2. We cannot disclose the original image due to privacy issues, so we release feature maps obtained by passing through the network.
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Accurate and efficient anomaly detection is a key enabler for the cognitive management of optical networks, but traditional anomaly detection algorithms are computationally complex and do not scale well with the amount of monitoring data. Therefore, this dataset enables research on new optical spectrum anomaly detection schemes that exploit computer vision and deep unsupervised learning to perform optical network monitoring relying only on constellation diagrams of received signals.
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Restored audio file using one-dimensional laser speckle image, which is voice of a male counting from zero to nine in English
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Original voice file of a male counting from zero to nine in English
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Animal recognition is an active research topic in recent years. Horse’s recognition is an important task in the world and in order to promote horse’s recognition research, the Tunisian Research Groups in Intelligent Machines of University of Sfax (REGIM of Sfax) will provide the Tunisian Horses DataBase of Regim Lab’2015 (THoDBRL’2015) freely of charge to mainly horses’ face recognition researchers and to increase total of researches done to enhance animal recognition. This Database is used in [1].
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Animal detection is an active research topic in recent years. Horse’s face detection is an important task in the world and in order to promote horse’s detection and recognition research, the REGIM-Lab.: REsearch Groups in Intelligent Machines, ENIS, University of Sfax, Tunisia will provide the Tunisian Horse Detection Database (THDD) freely of charge to mainly horses’ face detection researchers and to increase total of researches done to enhance animal detection.
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