Artificial Intelligence
This dataset is used for the identification of video in the internet traffic. The dataset was prepared by using Wireshark. It comprises of two types of traffic data, VPN (Virtual Private Network) or encrypted traffic data and Non-VPN or unencrypted traffic. The dataset consist of the data streams (.pcap) of 43 videos. Each video is played 50 times in both VPN and Non-VPN mode. The streams were obtained by setting-up a dummy client on a PC which plays a YouTube video and Wireshark is used to capture the internet traffic.
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The ReMouse dataset is collected in a guided environment, and it contains repeat sessions generated by the same human user(s). ReMouse dataset contains the mouse dynamics information of 100 users of mixed nationality, residing in diverse geographical regions and using different devices (hardware and software components).
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Ground Penetrating Radar (GPR) has a wide range of applications such as detection of buried mines, pipes and wires. GPR has been used as a near-surface remote sensing technique, and its working principle is based on electromagnetic (EM) wave theory. Here proposed data set is meant for data driven surrogate modelling based Buried Object Characterization. The considered problem of estimating geophysical parameters of a buried object is 2D. The training and testing scenarios include B-scan images (2D data), which contain 16 pairs of A-scan (concatenated forms of A-scans).
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This dataset includes the rotor geometrical parameters (*.csv) and motor parameters (*.csv) of interior permanent magnet synchronous motors. The rotor geometry covers three structures: 2D-, V-, and Nabla-structures. The motor parameters are generated by machine learning based on the finite element analysis results. The software JMAG Designer 19.1 was used for the finite element analysis.
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Dataset for paper "Integrating Machine Learning and Mathematical Optimization for Job Shop Scheduling"
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This dataset contains the test instances for the paper "A Matrix-cube-based Estimation of Distribution Algorithm for No-Wait Flow-Shop Scheduling with Sequence-Dependent Setup Times and Release Times".
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In this paper, we propose the first method to allow everyone to easily reconstruct their own 3D inner-body under clothing from a self-captured video with the mean reconstruction error of 0.73cm within 15s, avoiding privacy concerns arising from nudity or minimal clothing.
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This dataset consists of chest images of patients with different kinds of lung diseases.
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RIFIS is an image dataset that illustrates numerous aspects of rice field cultivation utilizing a walk-behind tractor. This dataset includes multiple movies, photos, and annotations. Moreover, location and orientation data are provided for the tractor during video and image recording.
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