Image Processing

Pedestrian detection has never been an easy task for computer vision and automotive industry. Systems like the advanced driver assistance system (ADAS) highly rely on far infrared (FIR) data captured to detect pedestrians at nighttime. The recent development of deep learning-based detectors has proven the excellent results of pedestrian detection in perfect weather conditions. However, it is still unknown what is the performance in adverse weather conditions.

274 views
  • Computer Vision
  • Last Updated On: 
    Wed, 01/22/2020 - 18:00

    It includes 312 ROIs. An ROI is a rectangular BMP image region. A rectangular image region  is located within a PDAC tumor region or within a HP region of a slice CT image. ROIs of 1-153 are PDAC, ROIs of 154:312 are HP.

    39 views
  • Artificial Intelligence
  • Last Updated On: 
    Fri, 04/10/2020 - 04:28

    The data set are images taken from the Particle Image Velocimetry (PIV) method and the Planar Laser-Induced Fluorescence (PLIF) method. These methods set 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.

    78 views
  • Image Processing
  • Last Updated On: 
    Thu, 03/26/2020 - 08:04

    [Now uploading... Total size is 300GB.]

    114 views
  • Image Processing
  • Last Updated On: 
    Sun, 01/19/2020 - 05:56

    Endoscopy is a widely used clinical procedure for the early detection of cancers in hollow-organs such as oesophagus, stomach, and colon. Computer-assisted methods for accurate and temporally consistent localisation and segmentation of diseased region-of-interests enable precise quantification and mapping of lesions from clinical endoscopy videos which is critical for monitoring and surgical planning. Innovations have the potential to improve current medical practices and refine healthcare systems worldwide.

  • Artificial Intelligence
  • Computer Vision
  • Image Processing
  • Machine Learning
  • Biomedical and Health Sciences
  • Medical Imaging
  • Last Updated On: 
    Sun, 03/29/2020 - 13:15

    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.

     

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

    Experimental results.

    48 views
  • Image Processing
  • Last Updated On: 
    Fri, 01/10/2020 - 02:53

    These three datasets cover Western, Chinese and Japanese food used for food instance counting and segmentation evaluation.

    101 views
  • Computer Vision
  • Last Updated On: 
    Mon, 01/06/2020 - 10:36

    Since there is no image-based personality dataset, we used the ChaLearn dataset for creating a new dataset that met the characteristics we required for this work, i.e., selfie images where only one person appears and his face is visible, labeled with the person's apparent personality in the photo.

    267 views
  • Artificial Intelligence
  • Last Updated On: 
    Thu, 01/02/2020 - 17:47

    We provide a dataset with synthetic white images for the Lytro Illum light field camera with precisely known microlens center coordinates.

    The dataset consists of white images taken at different zoom settings as well as different microlens array offset and rotation.

    The white images have been raytraced using a thin lens-based camera model. The synthesized white images incorporate natural as well as mechanical vignetting effects.

    156 views
  • Image Processing
  • Last Updated On: 
    Tue, 12/31/2019 - 09:03

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