Image Processing

This is a collection of 2D and 3D images used for grayscale image processing tests. It includes at least 8 images of each of the following sizes:

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The boring and repetitive task of monitoring video feeds makes real-time anomaly detection tasks difficult for humans. Hence, crimes are usually detected hours or days after the occurrence. To mitigate this, the research community proposes the use of a deep learning-based anomaly detection model (ADM) for automating the monitoring process.

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This datset contains 2000  images of size 256 X256. The dataset is created by captuirng photos using mobile phone. This dataset is applicable for two classes namely water and wet surface.

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1496 Views

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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2448 Views

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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2957 Views

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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1196 Views

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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75 Views

Original voice file of a male counting from zero to nine in English

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80 Views

Given the difficulty to handle planetary data we provide downloadable files in PNG format from the missions Chang'E-3 and Chang'E-4. In addition to a set of scripts to do the conversion given a different PDS4 Dataset.

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