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2007 Workshop on Intelligent Information Technology Application, IITA 2007

作者： Du, Weifeng Yue, Guangxue Cheng, Xu School of Information Engineering Jiaxing University Jiaxing 314001 China School of Computer and Communication Hunan University Changsha 410000 China Provincial Key Lab. of Image Processing and Imagecom Communication Nanjing University of Pos and Telecommunications Nanjing 210003 China

ISBN: (纸本)076953063X

In his paper, Prof. Ye Dongyi pointed out that the reduction approach introduced by Hu Xiaohua etc. will give wrong result in some situation. In this paper we come to a conclusion by analysis that the reduction approach is to keep boundary region partition unchangeable virtually. It is just different from the reduction approach given by Ye Dongyi. Then, we analyze the logic characteristic of boundary region partition reduction standard. © 2007 IEEE.

关键词： data reduction formal logic rough set theory boundary region partition reduction standard logic characteristics Rough set theory Formal logic data reduction boundary regions

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Attention State Assessment by Analyzing Electroencephalograph Signals

Attention State Assessment by Analyzing Electroencephalograp...

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International Congress on image and Signal processing, BioMedical Engineering and Informatics

作者： Junchang Zhao Xiaolin Huang Jun Wang Image Processing and Image Communications Key Lab Nanjing University of Posts & Telecomm Institute of Biomedical Electronic Engineering School of Electronic Science and Engineering Nanjing University

ISBN: (纸本)9781509037117

For brain function study, it is very important to assess the state of different attention conditions. In this paper, we study a cross-correlation between different attention electroencephalograph (EEG) signals by detrended cross-correlation analysis (DCCA). We use the method to study attention α wave EEG. And, we found that is possible to discriminate the cross-correlation between the meditation state of closing eyes and the absence of mind. It was found that the DCCA values of idle subjects' α wave EEG signals increased compared the meditating participants' α wave EEG signals. And it can be particularly helpful for treatment and brain development research.

关键词： meditation activity DCCA a wave

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Building a mixed-lingual neural TTS system with only monolingual data

arXiv

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arXiv 2019年

作者： Xue, Liumeng Song, Wei Xu, Guanghui Xie, Lei Wu, Zhizheng Shaanxi Provincial Key Lab of Speech and Image Information Processing School of Computer Science Northwestern Polytechnical University Xi'an China ***

When deploying a Chinese neural Text-to-Speech (TTS) system, one of the challenges is to synthesize Chinese utterances with English phrases or words embedded. This paper looks into the problem in the encoder-decoder framework when only monolingual data from a target speaker is available. Specifically, we view the problem from two aspects: speaker consistency within an utterance and naturalness. We start the investigation with an average voice model which is built from multispeaker monolingual data, i.e., Mandarin and English data. On the basis of that, we look into speaker embedding for speaker consistency within an utterance and phoneme embedding for naturalness and intelligibility, and study the choice of data for model training. We report the findings and discuss the challenges to build a mixed-lingual TTS system with only monolingual data. Copyright © 2019, The Authors. All rights reserved.

关键词： Embeddings

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An improved image dehazing algorithm based on dark channel prior

An improved image dehazing algorithm based on dark channel p...

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IEEE Workshop on Advanced Research and Technology in Industry Applications (WARTIA)

作者： Jiajie Liu Jieying Zheng Ziguan Cui Guijin Tang Feng Liu Jiangsu Province Key Lab on Image Processing & Image Communications Nanjing University of Posts and Telecommunications Nanjing China Ministry of Education Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (纸本)9781479969906

image dehazing algorithm based on dark channel prior has been proved to be effective, but it cannot still guarantee accurate transmission. To solve this problem, we firstly propose a more reasonable estimation of atmospheric light, because bias in the atmospheric light estimation will cause an inaccurate transmission. Secondly, we improve the estimation of transmission in bright area so as to alleviate color distortion. After image recovery, we carry out denoising to improve the image quality. Finally, we use a blind image quality assessment method based on property of Human Visual System, and the experimental results show that this improved algorithm is more effective.

关键词： Mathematical model Equations image color analysis Atmospheric modeling Estimation image quality Noise reduction

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Extraction method of microscopic moving particle basing on multimodal background model

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ICIC Express Letters, Part B: Applications 2015年第12期6卷 3153-3158页

作者： Zhang, Yanbin Yang, Zhangzhen Zhang, Hui Qin, Lei Image Processing and Image Communication Lab Jiangsu Key Lab of Wireless Communications Nanjing University of Posts and Telecommunications No. 66 New Mofan Road Nanjing210003 China Jiangsu Key Lab of Wireless Communications Nanjing University of Posts and Telecommunications No. 66 New Mofan Road Nanjing210003 China

Target extraction is a key technology for image measurement of moving particles distributed in fluidic system. In this paper, we propose a novel moving particle extraction method based on multimodal characteristic of the image. For the proposed particle extraction method, we firstly analyze the origin of multimodal characteristic of image background in the microscopic observation system, and then we design multimodal background model for particle extraction. For improving the performance of the model, we exploit the moving principle in the micro channel, and discuss the setting of learning rate. The experimental results demonstrate that the proposed methods achieve good performance compared with several traditional methods. © 2015, ICIC Express Letters Office. All rights reserved.

关键词： Extraction

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Modified color co-occurrence matrix for image retrieval

Modified color co-occurrence matrix for image retrieval

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First International Conference on Natural Computation, ICNC 2005

作者： Chang, Min Hyuk Pyun, Jae Young Ahmad, Muhammad Bilal Chun, Jong Hoon Park, Jong An Dept. of Information and Communications Engineering Chosun University Gwangju Korea Republic of Signal and Image Processing Lab. Dept. of Mechatronics Gwangju Institute of Science and Technology Gwangju Korea Republic of Dept. of Computer Information and Communication Eng. Jeonnam Provincial Collage Jeonnam Korea Republic of

Color correlogram for content-based image retrieval (CBIR) characterizes not only the color distribution of pixels, but also the spatial correlation of pairs of colors. Color not only reflects the material of surface, but also varies considerably with the change of illumination, the orientation of the surface, and the viewing geometry of the camera. The invariance to these environmental factors is not considered in most of the color features in color based CBIR including the color correlogram. However, pixels changed their color with almost same proportions with change of environmental factors. This fact is taken into consideration, and new algorithm is proposed. The color cooccurrence matrix for different spatial distances is defined based on the maximum/minimum of color component between the three components (R,G,B) of a pixel. The proposed algorithm has less number of features, and the change of illumination, etc. is also taken into account. © Springer-Verlag Berlin Heidelberg 2005.

关键词： image retrieval

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Analysis of alpha rhythm epileptic Electroencephalogram based on Inner composition alignment

Analysis of alpha rhythm epileptic Electroencephalogram base...

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2016 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics(AMEII 2016)

作者： Yiyi He Danqin Xing Jiaqin Wang Jia-Fei Dai Jun Wang Feng-Zhen Hou Image Processing and Image Communications Key Lab Nanjing Univ.of Posts & Telecomm. Nanjing General Hospital of Nanjing Military Command School of Science China Pharmaceutical University

ISBN: (纸本)9781510823808

The EEG signal is an important tool for the diagnosis and prediction of epilepsy due to EEG containing a large number of physiological and pathological *** on alpha rhythm multi-channel EEG(electroencephalogram),this paper applied inner composition alignment(IOTA) algorithm to construct brain functional network and visualize the network *** is to apply the algorithm to calculate and analyze IOTA coefficient,the node average degree and clustering coefficient of epileptic brain network for studying if epileptic brain network is significantly different from those of *** results show that IOTA coefficient of epileptic brain network obviously differs from the normal by calculating T testing with SPSS software,which proved that the effectiveness of the algorithm to distinguish IOTA coefficient of epileptic brain network.

关键词： alpha rhythm Electroencephalogram epileptic Inner composition alignment

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The complexity of occupational stress electroencephalogram

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Occupational Diseases and Environmental Medicine 2013年第1期1卷 1-3页

作者： Honger Tian Lili Cao Jun Wang Tian Xu Yongguo Zhan Ling Liu Image Processing and Image Communications Key Lab College of Geo & Bio Information Nanjing University of Posts & Tele- comm Nanjing China Key Laboratory of Environment Medicine and Engineering Ministry of Education School of Public Health Southeast University Nanjing China

It is an important method for using electroencephalogram (EEG) to detect and diagnose occupational Stress in clinical practice. In this paper, the complexity analysis method based on Jensen-Shannon Divergence was used to calculate the complexity of occupational stress electroencephalogram from students and *** study found that the complexity of nurses’ EEG was higher than that of students’ EEG. The result can be used to assisted clinical diagnosis.

关键词： Occupational Stress Electroencephalogram Students Nurses Jensen-Shannon Divergence

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3D-ANAS: 3D Asymmetric neural architecture search for fast Hyperspectral image classification

arXiv

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arXiv 2021年

作者： Zhang, Haokui Gong, Chengrong Bai, Yunpeng Bai, Zongwen Li, Ying the Shaanxi Provincial Key Lab of Speech and Image Information Processing School of Computer Science Northwestern Polytechnical University Xi’an710129 China

Hyperspectral images involve abundant spectral and spatial information, playing an irreplaceable role in land-cover classification. Recently, based on deep learning technologies, an increasing number of HSI classification approaches have been proposed, which demonstrate promising performance. However, previous studies suffer from two major drawbacks: 1) the architecture of most deep learning models is manually designed, relies on specialized knowledge, and is relatively tedious. Moreover, in HSI classifications, datasets captured by different sensors have different physical properties. Correspondingly, different models need to be designed for different datasets, which further increases the workload of designing architectures;2) the mainstream framework is a patch-to-pixel framework. The overlap regions of patches of adjacent pixels are calculated repeatedly, which increases computational cost and time cost. Besides, the classification accuracy is sensitive to the patch size, which is artificially set based on extensive investigation experiments. To overcome the issues mentioned above, we firstly propose a 3D asymmetric neural network search algorithm and leverage it to automatically search for efficient architectures for HSI classifications. By analysing the characteristics of HSIs, we specifically build a 3D asymmetric decomposition search space, where spectral and spatial information are processed with different decomposition convolutions. Furthermore, we propose a new fast classification framework, i,e., pixel-to-pixel classification framework, which has no repetitive operations and reduces the overall cost. Experiments on three public HSI datasets captured by different sensors demonstrate the networks designed by our 3D-ANAS achieve competitive performance compared to several state-of-the-art methods, while having a much faster inference speed. Code is available at: https://***/hkzhang91/3D-ANAS. © 2021, CC BY.

关键词： Pixels

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Job Stress Electroencephalogram Based on Jensen-Shannon Divergence

Job Stress Electroencephalogram Based on Jensen-Shannon Dive...

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2013 International Conference on Biological,Medical and Chemical Engineering(BMCE 2013)

作者： Hong-er TIAN Li-li CAO Yong-guo ZHAN Ling LIU Zi-hai JIAN Huannuer YASHENGBIEKE Aili KAIMIERDING Jian WU Zheng-bao ZHANG Zhi-qiang PAN Xi YANG Jun WANG Key Laboratory of Environment Medicine and Engineering Ministry of EducationSchool of Public HealthSoutheast University Image Processing and Image Communications Key Lab College of Geo & Bio InformationNanjing Univ of Posts & Telecomm

To prevent the occurrence of burnout and karoshi,we try to detect and diagnose job stress in clinical practice using electroencephalogram(EEG).The EEG data were taken from 12 graduate students and 12 nurses from a third-grade class-A hospital,which two groups have the different job *** sampling frequency was 200 Hz,and the complexity of the electroencephalogram and its dynamic range were calculated based on Jensen-Shannon Divergence.T test value of the two groups was equal to 4.414 which confidence probability is 0.001,indicating the Jensen-Shannon Divergence value of students is less than that of ***,groups with different degree of job stress can be non-destructively and more easily diagnosed by the complexity of EEG data compared with blood samples,which is conducive to the evaluation,prevention and intervention of job stress and health promotion.

关键词： Electroencephalogram Complexity Job Stress Jensen-Shannon divergence

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