Signal Processing
The dataset contains depth frames and skeleton joints collected using Microsoft Kinect v2 and acceleration samples provided by an IMU during the simulation of ADLs and falls.
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The dataset contains depth frames collected using Microsoft Kinect v1 in top-view configuration and can be used for fall detection.
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At the intersection of signal processing and information forensics, the Signal Processing Cup 2016 global competition has explored a time-varying location-dependent signature of power grids that can be intrinsically captured in media recordings. This signature is called the Electric Network Frequency (ENF) signals. Throughout the SP Cup 2016 competition, participants were provided with multiple training, practice, and testing datasets that consisted of recordings made in different grids and containing ENF traces.
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Several established parameters and metrics have been used to characterize the acoustics of a room. The most important are the Direct-To-Reverberant Ratio (DRR), the Reverberation Time (T60) and the reflection coefficient. The acoustic characteristics of a room based on such parameters can be used to predict the quality and intelligibility of speech signals in that room.
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Smartphones perform Wifi scans to adapt to the changing wireless environments causes by mobility. From network monitoring perspective, such scans provide a natural stream of network measurements from client's point of view. In order to see whether such measurements can provide new insights in monitoring large scale wireless networks, we collected the Wifi scan results data, together with other Wifi related logs, from the PhoneLab smartphone testbed over 5 months. All data are collected passively from the smartphones.
last modified: 2016-03-09
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