Communications

Our goal is to find whether a convolutional neural network (CNN) performs better than the existing blind algorithms for image denoising, and, if yes, whether the noise statistics has an effect on the performance gap. We performed automatic identification of noise distribution, over a set of nine possible distributions, namely, Gaussian, log-normal, uniform, exponential, Poisson, salt and pepper, Rayleigh, speckle and Erlang. Next, for each of these noisy image sets, we compared the performance of FFDNet, a CNN based denoising method, with noise clinic, a blind denoising algorithm.

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  • Communications
  • Last Updated On: 
    Fri, 03/01/2019 - 21:15

    Full Duplex Sensor array

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  • Communications
  • Last Updated On: 
    Thu, 02/28/2019 - 08:36

    Our Signing in the Wild dataset consists of various videos harvested from YouTube containing people signing in various sign languages and doing so in diverse settings, environments, under complex signer and camera motion, and even group signing. This dataset is intended to be used for sign language detection.

     

    188 views
  • Communications
  • Last Updated On: 
    Sat, 02/23/2019 - 10:49

    This dataset was generated on a small-scale process automation scenario using MODBUS/TCP equipment, for research on the application of ML techniques to cybersecurity in Industrial Control Systems. The testbed emulates a CPS process controlled by a SCADA system using the MODBUS/TCP protocol. It consists of a liquid pump simulated by an electric motor controlled by a variable frequency drive (allowing for multiple rotor speeds), which in its turn controlled by a Programmable Logic Controller (PLC).

    992 views
  • Communications
  • Last Updated On: 
    Thu, 01/31/2019 - 10:23

    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 We developed a packet sniffer application to capture IAT of packets.

    98 views
  • Communications
  • Last Updated On: 
    Sat, 02/02/2019 - 22:53

    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

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

    None

    51 views
  • Communications
  • Last Updated On: 
    Tue, 06/11/2019 - 18:24

    Design of novel RF front-end hardware architectures and their associated measurement algorithms.Research objectives, includes:RO1: Novel architecture based upon Adaptive Wavelet Band-pass Sampling (AWBS) of RF Analog-to-Information Conversion (AIC).RO2: Integration of AWBS for increasing the wideband sensing capabilities of real-time spectrum analyzers by using AICs.RO3: Propose online calibration methods and algorithms for front-end hardware non-idealities compensation.RO4: Design a hardware prototype aimed to perform real-time spectrum sensing with 1 GHz real-time bandwidth.

    82 views
  • Communications
  • Last Updated On: 
    Wed, 01/02/2019 - 14:01

    This dataset is related to the paper  "A distributed Front-end Edge node assessment method by using a learning-to-rank method"

     

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    71 views
  • Communications
  • Last Updated On: 
    Mon, 01/07/2019 - 18:56

    Radio frequency identification (RFID) provides a simple and effective solution to the passive indoor localization. The conventional wisdom about RFID localization is utilizing reference tags. It performs well in tag or single passive target localization. However, in the passive multiple target scenario, reference tag based localization suffers from some limitations, including the array aperture, mutual coupling of reference tags, and coherent superimposition of target signals.

    156 views
  • Communications
  • Last Updated On: 
    Wed, 01/23/2019 - 07:07

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