Machine Learning

monitoring, processing and prediction data

51 views
  • Machine Learning
  • Last Updated On: 
    Mon, 12/23/2019 - 20:42

    ArPC is an Arabic paraphrase identification corpus. It consists of 1331 sentence pairs along with their binary score that indicates weather the pairs are paraphrase or not. The corpus has been manually annotated by three Arabic native speakers.

    30 views
  • Artificial Intelligence
  • Last Updated On: 
    Sat, 12/21/2019 - 07:07

    The PMMW real-time imager, SAIR-U, is developed by Microwave Laboratory of Beihang University, China.It could be (or has been) used in non-contact, non-cooperative (i.e. no need for a fixed posture) security, especially in the environment of large passenger flow. This is the dataset used in the experiment in paper"Real-time Concealed Object Detection from Passive Millimeter Wave Images Based on YOLOv3 Algorithm"

    58 views
  • Machine Learning
  • Last Updated On: 
    Thu, 12/19/2019 - 10:53

    The PMMW real-time imager, SAIR-U, is developed by Microwave Laboratory of Beihang University, China.It could be (or has been) used in non-contact, non-cooperative (i.e. no need for a fixed posture) security, especially in the environment of large passenger flow. This is the dataset used in the experiment in paper"Real-time Concealed Object Detection from Passive Millimeter Wave Images Based on YOLOv3 Algorithm"

    12 views
  • Machine Learning
  • Last Updated On: 
    Thu, 12/19/2019 - 10:53

    The dataset corresponds to the variables that affect the process of passing the sheet between rodsizer and the spooner section for a paper machine.

    206 views
  • Machine Learning
  • Last Updated On: 
    Tue, 01/21/2020 - 14:54

    Research on damage detection of road surfaces has been an active area of research, but most studies have focused so far on the detection of the presence of damages. However, in real-world scenarios, road managers need to clearly understand the type of damage and its extent in order to take effective action in advance or to allocate the necessary resources. Moreover, currently there are few uniform and openly available road damage datasets, leading to a lack of a common benchmark for road damage detection.

    570 views
  • Artificial Intelligence
  • Last Updated On: 
    Tue, 01/21/2020 - 14:54

    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: 
    Fri, 02/21/2020 - 07:43

    The file 'GPS_P2.zip' is the dataset collected from the GNSS sensor of "Xinda" autonomous vehicle in the Connected Autonomous Vehicles Test Fields (the CAVs Test Fields) Weishui Campus,Chang'an University.

    The file 'fault.zip' is the simulated faults in the healthy data in '.mat' format, where X_abrupt, X_noise and X_drift represent abrupt faults, noise and drift in the long run are added into the healthy data, respectively.

    116 views
  • Machine Learning
  • Last Updated On: 
    Thu, 02/20/2020 - 03:50

    The Heidelberg Spiking Datasets comprise two spike-based classification datasets: The Spiking Heidelberg Digits (SHD) dataset and the Spiking Speech Command (SSC) dataset. The latter is derived from Pete Warden's Speech Commands dataset (https://arxiv.org/abs/1804.03209), whereas the former is based on a spoken digit dataset recorded in-house and included in this repository. Both datasets were generated by applying a detailed inner ear model to audio recordings. We distribute the input spikes and target labels in HDF5 format.

    277 views
  • Machine Learning
  • Last Updated On: 
    Tue, 01/21/2020 - 14:54

    The development of electronic nose (e-nose) for a rapid, simple, and low-cost meat assessment system becomes the concern of researchers in recent years. Hence, we provide time-series datasets that were recorded from e-nose for beef quality monitoring experiment. This dataset is originated from 12 type of beef cuts including round (shank), top sirloin, tenderloin, flap meat (flank), striploin (shortloin), brisket, clod/chuck, skirt meat (plate), inside/outside, rib eye, shin, and fat.

    80 views
  • IoT
  • Last Updated On: 
    Fri, 12/06/2019 - 05:37

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