computer vision

A composite dataset with eight videos (totaling the pronunciation of seventeen words, with intervals, sagittal plane, and gray scale), for experiments in computer vision, video processing, and articulation investigation of the vocal tract.

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  • Computer Vision
  • Last Updated On: 
    Wed, 02/05/2020 - 10:53

    Nextmed project is a software platform for the segmentation and visualization of medical images. It consist on a series of different automatic segmentation algorithms for different anatomical structures and  a platform for the visualization of the results as 3D models.

    This dataset contains the .obj and .nrrd files that correspond to the results of applying our automatic lung segmentation algorithm to the LIDC-IDRI dataset.

    This dataset relates to 718 of the 1012 LIDC-IDRI scans.

    125 views
  • Artificial Intelligence
  • Last Updated On: 
    Tue, 01/21/2020 - 15:00

    Dataset for Telugu Handwritten Gunintam

    162 views
  • Computer Vision
  • Last Updated On: 
    Fri, 11/29/2019 - 07:25

     

    Dataset was created as part of joint efforts of two research groups from the University of Novi Sad, which were aimed towards development of vision based systems for automatic identification of insect species (in particular hoverflies) based on characteristic venation patterns in the images of the insects' wings.The set of wing images consists of high-resolution microscopic wing images of several hoverfly species. There is a total of 868 wing images of eleven selected hoverfly species from two different genera, Chrysotoxum and Melanostoma.

    481 views
  • Computer Vision
  • Last Updated On: 
    Thu, 12/12/2019 - 13:38

    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.

     

    233 views
  • Communications
  • Last Updated On: 
    Sat, 02/23/2019 - 10:49

    Emergency  managers  of  today  grapple  with  post-hurricane damage assessment that is often labor-intensive, slow,costly,   and   error-prone.   As   an   important   first   step   towards addressing  the   challenge,   this   paper   presents   the   development of  benchmark  datasets  to  enable  the  automatic  detection  ofdamaged buildings from post-hurricane remote sensing imagerytaken  from  both  airborne  and  satellite  sensors.  Our  work  has two  major  contributions:  (1)  we  propose  a  scalable  framework to  create  benchmark  datasets  of  hurricane-damaged  buildings

    1274 views
  • Remote Sensing
  • Last Updated On: 
    Wed, 12/04/2019 - 09:51