Computer Vision

This archive contains images and labels for the Idly-Dosa-Vada (IDV) dataset, for use with Yolo (and Tensorflow) object detection frameworks.

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  • Computer Vision
  • Last Updated On: 
    Wed, 01/29/2020 - 21:59

    Understanding causes and effects in mechanical systems is an essential component of reasoning in the physical world. This work poses a new problem of counterfactual learning of object mechanics from visual input. We develop the COPHY benchmark to assess the capacity of the state-of-the-art models for causal physical reasoning in a synthetic 3D environment and propose a model for learning the physical dynamics in a counterfactual setting.

    36 views
  • Computer Vision
  • Last Updated On: 
    Mon, 01/27/2020 - 10:07

    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.

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

    ADAM is organized as a half day Challenge, a Satellite Event of the ISBI 2020 conference in Iowa City, Iowa, USA.

    58 views
  • Computer Vision
  • Last Updated On: 
    Mon, 01/20/2020 - 07:52

    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: 
    Tue, 02/11/2020 - 00:40

    The data set includes three sub-data sets, namely the DAGM2007 data set, the ground crack data set, and the Yibao bottle cap defect data set, which are divided into a training set and a test set, in which the positive and negative samples are unbalanced.

    61 views
  • Artificial Intelligence
  • Last Updated On: 
    Wed, 01/15/2020 - 05:59

    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: 
    Thu, 02/27/2020 - 10:07

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

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

    This is a small dataset as a part of huge dataset of breast cancer images. The images are mammograms. 

    135 views
  • Computer Vision
  • Last Updated On: 
    Fri, 12/27/2019 - 08:21

    The data made available are the simulations of a time-resolved Monte Carlo model for use in quantitative as well as qualitative analysis of different types of particle atmospheres.

    184 views
  • Computer Vision
  • Last Updated On: 
    Thu, 02/27/2020 - 10:07

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