The data set are images taken from the Particle Image Velocimetry (PIV) method and the Planar Laser-Induced Fluorescence (PLIF) method. These methods sets out the macro-scale experimental techniques that can enable fluid dynamic knowledge to inform molecular communication performance and design. Fluid dynamic experiments can capture latent features that allow the receiver to detect coherent signal structures and infer transmit parameters for optimal decoding.

  • Image Processing
  • Last Updated On: 
    Sat, 01/18/2020 - 12:29

    This dataset contains light-field microscopy images and converted sub-aperture images. 


    The folder with the name "Light-fieldMicroscopeData" contains raw light-field data. The file LFM_Calibrated_frame0-9.tif contains 9 frames of raw light-field microscopy images which has been calibrated. Each frame corresponds to a specific depth. The 9 frames cover a depth range from 0 um to 32 um with step size 4 um. Files with name LFM_Calibrated_frame?.png are the png version for each frame.


  • Image Processing
  • Last Updated On: 
    Thu, 02/27/2020 - 10:07

    Addtional datasets for the jounal paper subimitted to IEEE Transactions on Computational Imaging, including self-captured light field microscopy datasets with lab-assembled LF microscope.

  • Artificial Intelligence
  • Last Updated On: 
    Wed, 11/27/2019 - 22:19

    The odometric model is simulated herein. We described the trajectory of such one odometric model, with the delta of the heading angle given as one parameter of the simulation. The iterations show that the trajectory is well in the continuity of the variations of the heading angle. Moreover the distance in X and in Y are shown for the vehicle to be driven in the trajectory of the odometric model.

  • Transportation
  • Last Updated On: 
    Thu, 10/24/2019 - 07:06

    The dataset was built by capturing the static gestures of the American Sign Language (ASL) alphabet, from 8 people, except for the letters J and Z, since they are dynamic gestures. To capture the images, we used a Logitech Brio webcam, with a resolution of 1920 × 1080 pixels, in a university laboratory with artificial lighting. By extracting only the hand region, we defined an area of 400 × 400 pixels for the final image of our dataset.

  • Computer Vision
  • Last Updated On: 
    Tue, 01/07/2020 - 11:15

    RECOVERY-FA19 dataset is established for development and evaulation of retinal vessel detection algorithms in fluorescein angiography (FA). RECOVERY-FA19 provides ultra-widefield FA images acquired using Optos California P200DTx camera and labeled binary vessel maps.

  • Standards Research Data
  • Last Updated On: 
    Mon, 06/03/2019 - 15:22