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A multiple hypothesis tracking (MHT) algorithm based on multi-feature fusion is presented in this paper to counter range deception jammings. Sparse decomposition coefficients and bispectrum features are extracted to distinguish the targets and the jammings. A two-stage fusion structure using neural network and Dempster-Shafer evidence theory is designed to implement multi-feature fusion so as to get...
Fault diagnosis algorithm is an important part of power circuit. In order to improve the reliability of power circuit, this paper proposed a novel fault diagnosis algorithm with the dual-loop of Volterra filter. The algorithm utilized the dual-loop of Volterra filter to optimal the parameters of power circuit and remove the noise, then, predict the fault in power circuit by the revised parameters...
Deep Belief Network (DBN) learns the features of the raw data automatically, and develops a new idea for the study of fault analysis of High Speed Train (HST). Combining deep learning and classification ensemble technology, this paper presents a novel DBN hierarchical ensemble model for HST fault analysis. Firstly, Fast Fourier Transform (FFT) coefficients of the HST vibration signals are extracted...
Vigilance decrement happens in prolonged and monotonous tasks such as driving, therefore efficient estimation of vigilance using machine learning becomes a growing research field in road safety. However, the ground truth of vigilance level is often unknown. To address the estimation of brain states with unknown ground truth, we proposed an unsupervised manifold clustering method guided by task performance,...
In this paper, we explore the effects of noisy sounds (i.e. auditory stressor) on human stress using electrocardiogram (ECG) signals. The noisy sounds utilized in this study include: sound of car horn, children crying, siren, drilling and from a construction site. Essentially, the ECG signals are represented by eight heart rate variability features which are commonly utilized in human stress related...
In this paper, we proposed a driver drowsiness detection method for which only eyelid movement information was required. The proposed method consists of two major parts. 1) In order to obtain accurate eye openness estimation, a vision based eye openness recognition method was proposed to obtain an regression model that directly gave degree of eye openness from a low-resolution eye image without complex...
Feature extraction is one of key steps in fault diagnosis for High Speed Train (HST). In this work, we present a method that can automatically extract high-level features from HST vibration signals and recognize the faults. The method is composed of a Deep Belief Network (DBN) on Fast Fourier Transform (FFT) of vibration signals. DBNs can be trained greedily, layer by layer, using a model referred...
Identifying the presence of Anti-Nuclear Antibody in Human Epithelial type 2 (HEp-2) cells via Indirect Immunofluorescence (IIF) is commonly used to diagnose various connective tissue diseases in clinical pathology tests. This pathology test can be automated by computer vision algorithms. However, the existing automated systems, namely Computer Aided Diagnostic (CAD) systems, suffer from numerous...
Person re-identification on image sets in which each image is taken from a different angle and lighting condition is a very challenging task. This task becomes even more difficult when images are low resolution and carrying image compression artifacts. The accuracy of the existing re- identification techniques are relatively low on the challenging evaluation grounds such as VIPeR and iLIDS image datasets...
This paper presents a feature extraction algorithm combining S transform (ST) and two-directional two-dimensional principal component analysis ((2D)2 PCA) for partial discharge (PD) pattern recognition. S transform (ST) is firstly employed to obtain a time-frequency representation of the recorded UHF signals. Then, (2D)2 PCA is applied to compress the ST amplitude(STA) matrices to extract various...
Localizing license plate in an image enables vehicle detection and identification. Processing at high-definition (HD) image allows a better access of visual information but also enhances the necessity of multi-resolution analysis because license plates may appear in various sizes and shapes. A great computational burden is accompanied by processing the great number of candidate windows during multi-resolution...
This paper proposes a no-reference cross-layer video quality estimation model for low-resolution video over wireless networks. The estimation model contains two parts as feature processing and quality prediction. The first part covers the content-aware features, network layer features and application layer features. As for the content-awareness, by using the weighted Euclidean distance, the temporal...
A system of voiceprint identification under the Internet environment is discussed in this paper. Considering the limited storages of clients and the features of network transmission, Client/Server model is adopted in the system. In the client-side, feature parameters are extracted. This paper analyzes the performances with different parameters, and a new parameter (WPTMFC) and a mixed parameter under...
The current most STL(stereo lithography)format is widely used as a de facto industry standard in the rapid prototyping industry due to its simplicity and ability to tessellation of almost all surfaces, but some drawbacks such as precision loss, data redundancy and not conducive to concurrent design and the limitations of network synergy lead to unsatisfactory precision of the part in post processing...
Bayesian linear classifier is the basic scheme to solve model classification basing on statistics. Face with the classification of three different nectar plant, the near infrared spectrum data was acquired. The character of the near infrared spectrums is known as litter sample and higher dimension. In this paper, the method has developed to acquire the feature wavelength based on genetic algorithm...
The inherent nature of image and video and its multi-dimension data space makes its processing and interpretation a very complex task, normally requiring considerable processing power. Moreover, understanding the meaning of video content and storing it in a fast searchable and readable form, requires taking advantage of image processing methods, which when running them on a video stream per query,...
The working procedure model (WPM), which is composed by a set of models, is used to describe a process of a part made from roughcast to product. And the WPM plays a key role while part being produced. The process information comprises process drawing and process steps and shows a sequencing and asymptotic course that a part is made. The 3D model canpsilat be constructed automatically by the existing...
In this note, we present an approach for developing patient-specific 3D models of portal veins to provide geometric boundary conditions for computational fluid dynamics (CFD) simulations of the blood flow inside portal veins. The study is based on MRI liver images of individual patients to which we apply image registration and segmentation techniques and inlet and outlet velocity profiles acquired...
In this note, we present an approach for developing patient-specific 3D models of portal veins to provide geometric boundary conditions for computational fluid dynamics (CFD) simulations of the blood flow inside portal veins. The study is based on MRI liver images of individual patients to which we apply image registration and segmentation techniques and inlet and outlet velocity profiles acquired...
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