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The benchmark dataset  are consisted of 2,413 three-channel RGB images obtained from Google Earth satellite images and AID dataset.

  • Geoscience and Remote Sensing
  • Last Updated On: 
    Tue, 07/30/2019 - 10:03

    Device Fingerprinting for Access Control over a Campus and Isolated Network

    Device Fingerprinting (DFP) is a technique to identify devices using Inter-Arrival Time (IAT) of packets and without using any other unique identifier. Our experiments include generating graphs of IATs of 100 packets and using Convolutional Neural Network on the generated graphs to identify a device. We did two experiments where the first experiment was on Raspberri Pi and other experiment was on crawdad dataset.

     

    First Experiment: Raspberry Pi

  • Communications
  • Last Updated On: 
    Sat, 01/26/2019 - 09:08

    After a hurricane, damage assessment is critical to emergency managers and first responders so that resources can be planned and allocated appropriately. One way to gauge the damage extent is to detect and quantify the number of damaged buildings, which is traditionally done through driving around the affected area. This process can be labor intensive and time-consuming. In this paper, utilizing the availability and readiness of satellite imagery, we propose to improve the efficiency and accuracy of damage detection via image classification algorithms.

  • Geoscience and Remote Sensing
  • Last Updated On: 
    Thu, 12/13/2018 - 03:04

    A quantitative understanding of how sensory signals are transformed into motor outputs places useful constraints on brain function and helps reveal the brain's underlying computations. Here we present over 8,000 animal hours of behavior recordings to investigate the nematode C. elegans' response to time-varying mechanosensory signals. We use a high-throughput optogenetic assay, video microscopy and automated behavior quantification.

  • Neuroscience
  • Last Updated On: 
    Tue, 07/16/2019 - 11:19