Signal Processing
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 is the base data for paper "An Intelligent Recognition Method of a Short-Gap Arc in Aviation Cables Based on Feature Weight Enhancement".
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The data is divided into a training set of 999 images and a test set of 335 images. The size of each 2D ultrasound image is 800 by 540 pixels with a pixel size ranging from 0.052 to 0.326 mm. The pixel size for each image can be found in the csv files: ‘training_set_pixel_size_and_HC.csv’ and ‘test_set_pixel_size.csv’. The training set also includes an image with the manual annotation of the head circumference for each HC, which was made by a trained sonographer.
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Reverberation chamber (RC) is a metal cavity which is often used for EMC measurements. During the last couple of decades, RC has proved to be a useful tool for Over-the-air (OTA) measurements such as antenna efficiency, diversity gain, etc. A well stirred RC produces Rayleigh fading environment which is considered as a common test environment for testing and simulating performance of wireless devices such as mobile phones in GSM, WCDMA, UMTS and LTE frequency ranges.
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Presented are the target lists of a total of 8718 measurement frames produced by three (3) radar sensors, matched together with the IMU+GNSS-RTK solution for position and motion of two (2) automobiles. The sensors are synced in respect to their measurement times, but operate independently. Their modulation is offset by a certain frequency, to ensure mono-static evaluation. This allows for a cooperative evaluation of measurements. The sensor positions are static.
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This dataset contains the sEMG signals under low, medium, and high loads when 6 subjects performing ankle movements.
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Data and Reuslts from this work:
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This dataset has 2 different RFID manufacturer tags (2 of each) with different EPC content. Signal Strength data of all 4 tags were taken in the frequency spectrum in the US UHF (900-910 MHz) range. There are 100 data readings per tag, so 400 files total.
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The dataset image is the time-domain waveforms of the 7 fault states of the rolling bearing vibration signal, which provide research data for subsequent data processing and feature extraction.
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2113 Views