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histogram 2

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Histogram equalization using a reduced feature set of background speakers’ utterances for speaker recognition Article

Myung-jae KIM, Il-ho YANG, Min-seok KIM, Ha-jin YU

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 5,   Pages 738-750 doi: 10.1631/FITEE.1500380

Abstract: We propose a method for histogram equalization using supplement sets to improve the performance of speakerThe ranks of sample values for histogram equalization are estimated in ascending order from both themethods, such as cepstral mean normalization (CMN), cepstral mean and variance normalization (MVN), histogram

Keywords： Speaker recognition     Histogram equalization     i-vector    

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Statistical process control with intelligence using fuzzy ART neural networks

Min WANG, Tao ZAN, Renyuan FEI,

Frontiers of Mechanical Engineering 2010, Volume 5, Issue 2,   Pages 149-156 doi: 10.1007/s11465-010-0008-y

Abstract: With the automation development of manufacturing processes, artificial intelligence technology has been gradually employed to increase the automation and intelligence degree in quality control using statistical process control (SPC) method. In this paper, an SPC method based on a fuzzy adaptive resonance theory (ART) neural network is presented. The fuzzy ART neural network is applied to recognize the special disturbance of the manufacturing processes based on the classification on the histograms, which shows that the fuzzy ART neural network can adaptively learn the features of the histograms of the quality parameters in manufacturing processes. As a result, the special disturbance can be automatically detected when a feature of the special disturbance starts to appear in the histograms. At the same time, combined with spectrum analysis of the autoregressive model of quality parameters, the fuzzy ART neural network can also be utilized to adaptively detect the abnormal patterns in the control chart.

Keywords： statistical process control (SPC)     fuzzy adaptive resonance theory (ART)     histogram     control chart     time    

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Frequency-domain Analysis of ECG Signals

Tu Chengyuan,Zeng Yanjun,Li Shuxin

Strategic Study of CAE 2002, Volume 4, Issue 12,   Pages 66-70

Abstract:

A new simple approach to effectively detect QRS — T complexes in ECG curve is described, so as to easily get the P-wave (when AF does not happen) or the f-wave (when AF happens). By means of signal processing techniques such as the power spectrum function, the auto-correlation function and cross-correlation function, two kinds of ECG signals when AF does or does not happen were successively analyzed, showing the evident differences between them.

Keywords： ECG curve     P-wave     f-wave     AF (atrial fibrillation)     histogram     power spectrum     autocorrelation     cross-correlation    

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Detection of engineering vehicles in high-resolution monitoring images

Xun Liu, Yin Zhang, San-yuan Zhang, Ying Wang, Zhong-yan Liang, Xiu-zi Ye,star.liuxun@gmail.com,yinzh@zju.edu.cn,syzhang@zju.edu.cn,maggiewang0427@gmail.com

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 5,   Pages 346-357 doi: 10.1631/FITEE.1500026

Abstract: This paper presents a novel formulation for detecting objects with articulated rigid bodies from high-resolution monitoring images, particularly . There are many pixels in high-resolution monitoring images, and most of them represent the background. Our method first detects object patches from monitoring images using a coarse detection process. In this phase, we build a descriptor based on histograms of oriented gradient, which contain color frequency information. Then we use a linear support vector machine to rapidly detect many image patches that may contain object parts, with a low false negative rate and a high false positive rate. In the second phase, we apply a refinement classification to determine the patches that actually contain objects. In this stage, we increase the size of the image patches so that they include the complete object using models of the object parts. Then an accelerated and improved salient mask is used to improve the performance of the dense scale-invariant feature transform descriptor. The detection process returns the absolute position of positive objects in the original images. We have applied our methods to three datasets to demonstrate their effectiveness.

Keywords： Object detection     Histogram of oriented gradient (HOG)     Dense scale-invariant feature transform (dense    

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Title Author Date Type Operation

Histogram equalization using a reduced feature set of background speakers’ utterances for speaker recognition

Myung-jae KIM, Il-ho YANG, Min-seok KIM, Ha-jin YU

Journal Article

Statistical process control with intelligence using fuzzy ART neural networks

Min WANG, Tao ZAN, Renyuan FEI,

Journal Article

Frequency-domain Analysis of ECG Signals

Tu Chengyuan,Zeng Yanjun,Li Shuxin

Journal Article

Detection of engineering vehicles in high-resolution monitoring images

Xun Liu, Yin Zhang, San-yuan Zhang, Ying Wang, Zhong-yan Liang, Xiu-zi Ye,star.liuxun@gmail.com,yinzh@zju.edu.cn,syzhang@zju.edu.cn,maggiewang0427@gmail.com

Journal Article