Computer Vision

Double-identity fingerprint is a fake fingerprint created by aligning two fingerprints for maximum ridge similarity and then joining them along an estimated cutline such that relevant features of both fingerprints

are present on either sides of the cutline. The fake fingerprint containing the features of the criminal and his innocuous accomplice can be enrolled with an electronic machine readable travel document and later used to cross the automated

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  • Computer Vision
  • Last Updated On: 
    Fri, 02/14/2020 - 04:42

    Semantic Segmentation Image

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  • Computer Vision
  • Last Updated On: 
    Sat, 02/08/2020 - 06:36

    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

    Conveyor belts are the most widespread means of transportation for large quantities of materials in the mining sector. This dataset contains 388 images of structures with and without dirt buildup.

    One can use this dataset for experimentation on classifying the dirt buildup.

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  • Artificial Intelligence
  • Last Updated On: 
    Wed, 01/29/2020 - 18:54

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

    167 views
  • 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.

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  • 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.

    271 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.

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  • 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: 
    Sun, 03/29/2020 - 13:15

    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.

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

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