Machine Learning

Dataset consists of various open GIS data from the Netherlands as Population Cores, Neighbhourhoods, Land Use, Neighbourhoods, Energy Atlas, OpenStreetMaps, openchargemap and charging stations. The data was transformed for buffers with 350m around each charging stations. The response variable is binary popularity of a charging pool.

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  • Machine Learning
  • Last Updated On: 
    Thu, 10/31/2019 - 07:05

    The Contest: Goals and Organisation

     The 2019 Data Fusion Contest, organized by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (GRSS), the Johns Hopkins University (JHU), and the Intelligence Advanced Research Projects Activity (IARPA), aimed to promote research in semantic 3D reconstruction and stereo using machine intelligence and deep learning applied to satellite images.

    288 views
  • Computer Vision
  • Last Updated On: 
    Mon, 11/18/2019 - 09:55

    Attempts to prevent invasion of marine biofouling on marine vessels are demanding. By developing a system to detect marine fouling on vessels in an early stage of fouling is a viable solution. However, there is a  lack of database for fouling images for performing image processing and machine learning algorithm.

    78 views
  • Artificial Intelligence
  • Last Updated On: 
    Wed, 10/30/2019 - 10:06

    This is a reservoir dataset including a large number of figures. Reservoir simulation, an important part of the petroleum industry, a powerful tool helping oil companies understand the reservoir better.

    In this dataset, there more than 10,000 figures are showing in different period oilfield development. From the beginning to the end, we keep some variables constant while some changes to make clear the influences of different parts.

  • Machine Learning
  • Energy
  • Last Updated On: 
    Wed, 10/30/2019 - 03:16

    The Contest: Goals and Organization

     

    The 2017 IEEE GRSS Data Fusion Contest, organized by the IEEE GRSS Image Analysis and Data Fusion Technical Committee, aimed at promoting progress on fusion and analysis methodologies for multisource remote sensing data.

     

    102 views
  • Computer Vision
  • Last Updated On: 
    Tue, 10/29/2019 - 09:58

    This dataset includes the measurements of a simulated vehicle inside a Gazebo simulation using different sensors: a simulated UWB tag, a IMU and a PX4Flow. 

    57 views
  • Machine Learning
  • Last Updated On: 
    Mon, 10/28/2019 - 13:54

    Iris recognition has been an interesting subject for many research studies in the last two decades and has raised many challenges for the researchers. One new and interesting challenge in the iris studies is gender recognition using iris images. Gender classification can be applied to reduce processing time of the identification process. On the other hand, it can be used in applications such as access control systems, and gender-based marketing and so on. To the best of our knowledge, only a few numbers of studies are conducted on gender recognition through analysis of iris images.

    372 views
  • Artificial Intelligence
  • Last Updated On: 
    Thu, 10/31/2019 - 09:48

    In order to increase the diversity in signal datasets, we create a new dataset called HisarMod, which includes 26 classes and 5 different modulation families passing through 5 different wireless communication channel. During the generation of the dataset, MATLAB 2017a is employed for creating random bit sequences, symbols, and wireless fading channels. 

     

    162 views
  • Artificial Intelligence
  • Last Updated On: 
    Tue, 11/12/2019 - 08:05

    The Data Fusion Contest 2016: Goals and Organization

    The 2016 IEEE GRSS Data Fusion Contest, organized by the IEEE GRSS Image Analysis and Data Fusion Technical Committee, aimed at promoting progress on fusion and analysis methodologies for multisource remote sensing data.

    New multi-source, multi-temporal data including Very High Resolution (VHR) multi-temporal imagery and video from space were released. First, VHR images (DEIMOS-2 standard products) acquired at two different dates, before and after orthorectification:

    190 views
  • Computer Vision
  • Last Updated On: 
    Fri, 10/25/2019 - 11:22

    Each database (*.db) contain three columns. First column: date and time of the tweet, second column: tweet, third column: sentiment score for the particular tweet within the range [-1,1] with -1 being the most negative, 0 being the neutral and +1 being the most positive sentiment.

    3133 views
  • Artificial Intelligence
  • Last Updated On: 
    Sat, 11/23/2019 - 22:51

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