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In this letter, an improved kernel density estimation (KDE) constant false alarm rate (CFAR) method is proposed for ship detection in single polarization synthetic aperture radar (SAR) images. The proposed method consists of a target enhancement filter, an adaptive KDE bandwidth estimation method and an improved KDE-CFAR. The gravity-based target enhancement filter is utilized to remove the inhomogeneity...
The loop-stage-dependent exchange bias training effect has been systematically studied in the polycrystalline FeNi/FeMn bilayers. According to the ferromagnet (FM) magnetization states, an entire magnetic hysteresis loop can be divided into four different stages: 1) positive saturation stage; 2) descending branch; 3) negative saturation stage; and 4) ascending branch. The loop-stage-dependent training...
This paper presents our system designed for MSR-Bing Image Retrieval Challenge @ ICME 2014. The core of our system is formed by a text processing module combined with a module performing PCA-assisted perceptron regression with random sub-space selection (P2R2S2). P2R2S2 uses Over-Feat features as a starting point and transforms them into more descriptive features via unsupervised training. The relevance...
Automatic face recognition in unconstrained environments is a challenging task. To test current trends in face recognition algorithms, we organized an evaluation on face recognition in mobile environment. This paper presents the results of 8 different participants using two verification metrics. Most submitted algorithms rely on one or more of three types of features: local binary patterns, Gabor...
The measurements for breakdown voltages have been made with point-plane electrodes for high-pressure carbon dioxide up to supercritical conditions at different temperatures. The breakdown voltages depend on electrode gap, temperature and pressure of gas while preserving the intrinsic nonlinear combination of these characteristics. Artificial neural network was used to model the complex nonlinear relationship...
Semi-supervised classification methods utilize unlabeled data to help learn better classifiers, when only a small amount of labeled data is available. Many semi-supervised learning methods have been proposed in the past decade. However, some questions have not been well answered, e.g., whether semi-supervised learning methods outperform base classifiers learned only from the labeled data, when different...
This paper deals with the problem of time-varying (TV) channel estimation for multiple-input multiple-output/orthogonal frequency-division multiplexing (MIMO/OFDM) systems based on superimposed training (ST). The time-varying coefficients of the TV channel are firstly modeled by truncated discrete Fourier bases, and then optimally estimated both in one OFDM symbols and over multiple OFDM symbols by...
The idea of this research is to determine can we tell from the HRV data without paroxysmal atrial fibrillation present at the recording if the patient suffers from this arrhythmia. The benefit is we can provide time and cost effective preliminary screening procedure during short time visit to the clinic. To achieve this goal we used Fourier analysis of the 30 minute HRV segment duration. We found...
The idea of this research is to determine how long in advance can we predict the onset of paroxysmal atrial fibrillation (PAF) from the HRV data. Having established such methods with great confidence it is possible to avert the PAF onset using pacing techniques, thus reliving patient pains.
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