Signal Processing
The SWINSEG dataset contains 115 nighttime images of sky/cloud patches along with their corresponding binary ground truth maps The ground truth annotation was done in consultation with experts from Singapore Meteorological Services. All images were captured in Singapore using WAHRSIS, a calibrated ground-based whole sky imager, over a period of 12 months from January to December 2016. All image patches are 500x500 pixels in size, and were selected considering several factors such as time of the image capture, cloud coverage, and seasonal variations.
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The dataset, includes raw data, observations and biometric data from our case study with an individual with DMD, controlling for the first time an active hand orthosis.
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1260 Views
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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2820 Views
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.
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740 Views
The steganography and steganalysis of audio, especially compressed audio, have drawn increasing attention in recent years, and various algorithms are proposed. However, there is no standard public dataset for us to verify the efficiency of each proposed algorithm. Therefore, to promote the study field, we construct a dataset including 33038 stereo WAV audio clips with a sampling rate of 44.1 kHz and duration of 10s. And, all audio files are from the Internet through data crawling, which is for a better simulation of a real detection environment.
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3394 Views
This dataset collection contains eleven datasets used in Locally Linear Embedding and fMRI feature selection in psychiatric classification.
The datasets given in the Links section are reduced subsets of those contained in their respective tar files (a consequence of Mendeley Data's 10GB limitation).
The Linked datasets (not the tar files) contain just the MATLAB file and the resting state image (or block-design fMRI for the MRN dataset), where appropriate.
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846 Views
This paper presents a road vehicle recognition and classification approach for intelligent transportation systems. This approach uses a roadside installed low cost magnetometer and associated data collection system. The system measures the magnetic field changing, detects passing vehicles and recognizes vehicle types.
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605 Views
This code was used in some previous our articles, such as:
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125 Views
See .doc-fie in the attachement.
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110 Views
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.
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269 Views