Signal Processing

      The following dataset consists of utterances, recorded using 24 volunteers raised in the Province of Manitoba, Canada. To provide a repeatable set of test words that would cover all of the phonemes, the Edinburg Machine Readable Phonetic Alphabet (MRPA) [KiGr08], consisting of 44 words is used. Each recording consists of one word uttered by the volunteer and recorded in one continuous session.

  • Signal Processing
  • Last Updated On: 
    Thu, 11/08/2018 - 10:34
    Citation Author(s): 
    Sina Sedigh, Witold Kinsner

    This dataset is associated with the paper, Jackson & Hall 2016, which is open source, and can be found here: http://ieeexplore.ieee.org/document/7742994/

    The DataPort Repository contains the data used primarily for generating Figure 1.

  • Biomedical and Health Sciences
  • Neuroscience
  • Biophysiological Signals
  • Brain
  • Signal Processing
  • Last Updated On: 
    Sat, 06/16/2018 - 23:05
    Citation Author(s): 
    Andrew Jackson, Thomas M. Hall

    The distributed generation, along with the deregulation of the Smart Grid, have created a great concern on Power Quality (PQ), as it has a direct impact on utilities and customers, as well as effects on the sinusoidal signal of the power line. The a priori unknown features of the distributed energy resources (DER) introduce non-linear behaviours in loads associated to a variety of PQ disturbances.

  • Power and Energy
  • Smart Grid
  • Signal Processing
  • Other
  • Last Updated On: 
    Thu, 11/08/2018 - 10:34
    Citation Author(s): 
    Olivia Florencias-Oliveros, M. J. Espinosa-Gavira, Juan-José González de la Rosa, A. Agüera-Pérez, José Carlos Palomares-Salas, J. M. Sierra-Fernández

    We study the Picture-level Just Noticeable Difference (PJND) of symmetrically and asymmetrically compressed stereoscopic images for JPEG2000 and H.265 intra coding. We conduct interactive subjective quality assessment tests to determine the PJND point using both a pristine image and a distorted image as a reference.

  • Signal Processing
  • Last Updated On: 
    Wed, 05/15/2019 - 22:31

    The files contain the research data. The noisy unprocessed audio data and processed audio data using the proposed speech enhancement method are uploaded. 

  • Standards Research Data
  • Wearable Sensing
  • Signal Processing
  • Last Updated On: 
    Thu, 05/09/2019 - 13:57

    Two files are provided. In the first one, there are the power signals obtained from the current and voltage measurements made with our own acquisition system (with a sampling frequency of 5 kHz). They correspond to the switching on and off of 12 home electrical appliances randomly switched on and off during 1 hour by using relay modules and resulting in 1200 events.

    In the second file, the time instants of these events are all reported.

  • Smart Grid
  • Signal Processing
  • Last Updated On: 
    Wed, 05/01/2019 - 09:35

    The SWINSEG dataset contains 115 nighttime images of sky/cloud patches along with their corresponding binary ground truth maps The ground truth annotation was done in consultation with experts from Singapore Meteorological Services. All images were captured in Singapore using WAHRSIS, a calibrated ground-based whole sky imager, over a period of 12 months from January to December 2016. All image patches are 500x500 pixels in size, and were selected considering several factors such as time of the image capture, cloud coverage, and seasonal variations.

     

  • Energy
  • Remote Sensing
  • Geoscience and Remote Sensing
  • Environmental
  • Signal Processing
  • Last Updated On: 
    Thu, 04/04/2019 - 10:06

    The dataset, includes raw data, observations and biometric data from our case study with an individual with DMD, controlling for the first time an active hand orthosis.

  • Biomedical and Health Sciences
  • Neuroscience
  • Biophysiological Signals
  • Signal Processing
  • Last Updated On: 
    Wed, 03/13/2019 - 11:40

    Our goal is to find whether a convolutional neural network (CNN) performs better than the existing blind algorithms for image denoising, and, if yes, whether the noise statistics has an effect on the performance gap. We performed automatic identification of noise distribution, over a set of nine possible distributions, namely, Gaussian, log-normal, uniform, exponential, Poisson, salt and pepper, Rayleigh, speckle and Erlang. Next, for each of these noisy image sets, we compared the performance of FFDNet, a CNN based denoising method, with noise clinic, a blind denoising algorithm.

  • Communications
  • Computational Intelligence
  • Signal Processing
  • Last Updated On: 
    Fri, 03/01/2019 - 21:15

    Our Signing in the Wild dataset consists of various videos harvested from YouTube containing people signing in various sign languages and doing so in diverse settings, environments, under complex signer and camera motion, and even group signing. This dataset is intended to be used for sign language detection.

     

  • Communications
  • Computational Intelligence
  • Signal Processing
  • Last Updated On: 
    Sat, 02/23/2019 - 10:49

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