Image Fusion

Depths to the various subsurface anomalies have been the primary interest in all the applications of magnetic methods of geophysical prospection. Depths to the subsurface geologic features of interest are more valuable and superior to all other properties in any correct subsurface geologic structural interpretations.

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  • Machine Learning
  • Last Updated On: 
    Mon, 06/08/2020 - 14:41

    This is a collection of paired thermal and visible ear images. Images in this dataset were acquired in different illumination conditions ranging between 2 and 10700 lux. There are total 2200 images of which 1100 are thermal images while the other 1100 are their corresponding visible images. Images consisted of left and right ear images of 55 subjects. Images were capture in 5 illumination conditiond for every subjects. This dataset was developed for illumination invariant ear recognition study. In addition it can also be useful for thermal and visible image fusion research.

     

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  • Image Processing
  • Last Updated On: 
    Sat, 05/23/2020 - 05:49

    This is a dataset having paired thermal-visual images collected over 1.5 years from different locations in Chitrakoot, India and Prayagraj, India. The images can be broadly classified into greenery, urban, historical buildings and crowd data.

    The crowd data was collected from the Maha Kumbh Mela 2019, Prayagraj, which is the largest religious fair in the world and is held every 12 years.

    64 views
  • Computer Vision
  • Last Updated On: 
    Wed, 02/26/2020 - 07:37

    The 2020 Data Fusion Contest, organized by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (GRSS) and the Technical University of Munich, aims to promote research in large-scale land cover mapping based on weakly supervised learning from globally available multimodal satellite data. The task is to train a machine learning model for global land cover mapping based on weakly annotated samples.

  • Artificial Intelligence
  • Machine Learning
  • Image Fusion
  • Geoscience and Remote Sensing
  • Last Updated On: 
    Thu, 05/28/2020 - 11:57

    The dataset contains high-resolution microscopy images and confocal spectra of semiconducting single-wall carbon nanotubes. Carbon nanotubes allow down-scaling of electronic components to the nano-scale. There is initial evidence from Monte Carlo simulations that microscopy images with high digital resolution show energy information in the Bessel wave pattern that is visible in these images. In this dataset, images from Silicon and InGaAs cameras, as well as spectra, give valuable insights into the spectroscopic properties of these single-photon emitters.

    364 views
  • Artificial Intelligence
  • Last Updated On: 
    Thu, 12/12/2019 - 13:43

    Multi-modal Exercises Dataset is a multi- sensor, multi-modal dataset, implemented to benchmark Human Activity Recognition(HAR) and Multi-modal Fusion algorithms. Collection of this dataset was inspired by the need for recognising and evaluating quality of exercise performance to support patients with Musculoskeletal Disorders(MSD).The MEx Dataset contains data from 25 people recorded with four sensors, 2 accelerometers, a pressure mat and a depth camera.

    506 views
  • Computer Vision
  • Last Updated On: 
    Tue, 10/01/2019 - 10:57

     

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  • Image Processing
  • Last Updated On: 
    Mon, 07/08/2019 - 08:21

    3D-videos database.

    46 views
  • Image Fusion
  • Last Updated On: 
    Tue, 03/19/2019 - 20:40

    Changes in left ventricular (LV) aggregate cardiomyocyte  orientation and deformation underlie cardiac function and dysfunction. As such, in vivo aggregate cardiomyocyte "myofiber" strain has mechanistic significance, but currently there exists no established technique to measure in vivo cardiomyocyte strain.

     

    211 views
  • Health
  • Last Updated On: 
    Tue, 01/29/2019 - 20:39

    This code was used in some previous our articles, such as:

    51 views
  • Image Fusion
  • Last Updated On: 
    Wed, 01/16/2019 - 03:45

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