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11th IEEE International Conference on Advanced Infocomm Technology, ICAIT 2019

作者： Hu, Xinmei Yuan, Qi Shandong Normal University Shandong Province Key Laboratory of Medical Physics and Image Processing Technology Jinan250358 China

ISBN: (纸本)9781728147789

Automatic seizure detection has significance for the diagnosis of epilepsy and the reduction of massive workload for neuroscientists. In the analysis of electroencephalogram (EEG) to achieving the goal of detecting seizure activity automatically, in this paper, we proposed a novel algorithm. First, the original signal is filtered into a band-pass filter and the linear features are calculated;Then, deep neural network - bidirectional long-short term memory network (Bi-LSTM) is used to train and classify features. Ultimately, obtained the specificity is 97.14%, the sensitivity is 100%, the G-mean is 98.56% and the average accuracy is 98.56%. The experimental results show that the proposed method has good performance and potential for clinical application. © 2019 IEEE.

关键词： Long short-term memory

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Appearance model based moving object matching across disjoint camera views

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2nd International Conference on Opto-Electronics Engineering and Materials Research, OEMR 2013

作者： Yu, Kong Shuai Hu, Dong Education Ministry's Key Lab of Broadband Wireless Communication and Sensor Network Technology The key lab of image processing and image communications of Jiangsu Province Nanjing University of Posts and Telecom Nanjing 210003 China

ISBN: (纸本)9783037857731

A new object tracking scheme for multi-camera surveillance with non-overlapping views is proposed in this paper. Brightness transfer function (BTF) is used to establish relative appearance correspondence between different views. Mixtures of probabilistic principal component analysis (MPPCA) is incooperated to learn the subspace of brightness transfer function with the concern to deal with multiple different brightness areas in a scene. The incremental major color spectrum histogram (IMCSH) is used as similarity measure for reliable matching. Experimental results with real world videos show the effectiveness of the proposed algorithm. © (2013) Trans Tech Publications, Switzerland.

关键词： Luminance

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A Novel Method to Get Super-Resolution images from Low-Resolution Compressed Video

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The Journal of China Universities of Posts and Telecommunications 2005年第2期12卷 50-54页

作者： ZHOU Liang ZHU Xiu-chang Information Industry Ministry and Jiangsu Province Key Lab of Image Processing and Image Communication Nanjing University of Posts and Communications Nanjing 210003 P. R. China

In order to resolve the problems of discontented restoration effect and confined applying scope which exist in the current compressed video restoration algorithms, a novel method to get super-resolution images from low-resolution compressed video is proposed in this paper. At first, a uniform model is presented and the restoration problem in the Bayesian framework is formulated under the MAP criterion, then the focus is put on the hybrid motion-compensation and transform coding schemes, at last the methods of getting the parameters are provided. The results of the simulation clearly demonstrate that our method not only has the properties of finer vision effect and wider applying scope, but also performs better than those of current classical algorithms in the aspects of Peak Signal Noise Ratio （PSNR） under the basis of the same condition.

关键词： super-resolutlon compressed video restoration

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Contour extraction model introducing contrast adaptive characteristics based on visual pathway

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Multimedia Tools and Applications 2024年 1-25页

作者： Fang, Tao Cai, Zhefei Fan, Yingle College of Electronics and Information Hangzhou Dianzi University Hangzhou310018 China Zhejiang Provincial Key Laboratory of Information Processing Communication and Networking Hangzhou310027 China Laboratory of Pattern Recognition and Image Processing Hangzhou Dianzi University Hangzhou310018 China

Effectively extracting image subject contours holds significant importance for subsequent image processing tasks. Recognizing the pivotal role of contrast features in contour characterization, this paper proposes a novel contour extraction model with contrast adaptive characteristics, inspired by visual perception simulation visual pathways. Firstly, leveraging the color antagonism traits of retinal ganglion cells, we construct a color image contrast calculation model to enhance the representation of visual information contrast. Furthermore, drawing upon the feed-forward impact of the retina on Lateral Geniculate Nucleus (LGN) cells, we introduce a contrast gain control mechanism to extract multi-directional primary contour responses. Secondly, employing the LIF neuron network to simulate the lateral geniculate body's information flow processing mechanism, we encode visual information via pulse firing to eliminate redundant contour details. Then, by considering the primary visual cortex (V1) cell's receptive field size variation with contrast, we devise a contrast-adaptive dynamic receptive field model. Additionally, we develop a texture suppression model based on the orientation/contrast disparity between the receptive field model's center and periphery. Finally, integrating the primary contour response and the image obtained through the inhibition model, we fuse features to derive the final image subject target contour. This study employs the BSDS500 dataset and the RuG40 dataset for experimentation. Comparative analysis against mainstream methods demonstrates our approach's superior ability to retain the main image outline while suppressing non-edge textures, with P-value indicators for contour detection of 0.58 and 0.50, respectively. Furthermore, visual analysis using box and whisker plots confirms the robustness of our proposed method. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Textures

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Adaptive double-buffered rate smoothing method for scalable network transmission of stereo video

Adaptive double-buffered rate smoothing method for scalable ...

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2010 International Conference on Audio, Language and image processing, ICALIP 2010

作者： Gu, Feng Sun, Jun Zhou, Jun Institute of Image Communication and Information Processing Shanghai Jiaotong University Shanghai Key Laboratory of Digital Media Processing and Transmissions 200240 Shanghai China

ISBN: (纸本)9781424458653

We study on the transmission of stereo videos over network. Because stereoscopic displays do not come into wide use, we need to separate the stereo video depending on the classification of views to satisfy different terminal displays when we transport the video over network. This transporting method of stereo video in Internet is called the view scalable transmission [1]. But there comes one question, the rate jitter of different views will become much larger in this transmitting method. So in this paper, we propose an adaptive double-buffered rate smoothing method to solve the problem. Experiment results validate our studies on the effects of dealing with rate jitter. ©2010 IEEE.

关键词： Jitter

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Error concealment for stereoscopic images using mode selection

Error concealment for stereoscopic images using mode selecti...

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International Symposium on Intelligent Signal processing and communications Systems

作者： Song, Lijuan Zhu, Xiuchang State Grid Electric Power Research Institute Nanjing 210003 China Jiangsu Province Key Lab. on Image Processing and Image Communication Nanjing University of Posts and Telecommunications Nanjing 210003 China

ISBN: (纸本)9781424473717

In this paper, a novel error concealment (EC) method for compressed stereoscopic image pairs is presented, which contains a new binocular EC mode and an improved monocular EC mode. The proposed algorithm selects appropriate EC mode to conceal the error block (EB) in the stereoscopic image according to the local characteristic of the EB. The experimental results demonstrate that the proposed scheme has good subjective and objective EC performance in stereoscopic images as compared to monocular mode. © 2010 IEEE.

关键词： Errors

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Dense Connected Residual Generative Adversarial Network for Single image Deblurring 5

Dense Connected Residual Generative Adversarial Network for ...

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5th IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2021

作者： Qian, Pan Wu, Yeyun Zhang, Xiaofeng Nanchang Hangkong University School of Information Engineering Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition Nanchang China

Recently, deep convolutional learning has been applied to image deblurring, which greatly improves the performance of single-image blind deblurring algorithms. However, most deep image deblurring models based on convolutional neural networks do not make full use of the information of low-level spatial convolutions, so they achieve relatively poor performance. In this paper, we improved the generator of the Generative Adversarial Network (GAN) and proposed dense networks and residual networks to solve this problem in image deblurring. The network makes full use of the hierarchical features of all convolutional layers. Specifically, we extract the local features of the convolutional layer through the proposed densely connected convolutional layer. Moreover, the dense connections of the residual dense network can connect all layers from the previous state to the current state. Then using local jump connection and feature fusion, it can adaptively learn more effective features from the previous and current local features, making the trained network more extensive. After fully obtaining the dense local features, the global residual connection is used to learn the global feature information in an overall manner. Experimental comparison and verification have proved the effectiveness of our method and achieved excellent results both quantitatively and qualitatively. © 2021 IEEE.

关键词： Generative adversarial networks

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Spectral unmixing for hyperspectral image classification with an adaptive endmember selection

Spectral unmixing for hyperspectral image classification wit...

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4th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2013

作者： Meng, Qingjie Zhang, Yanning Wei, Wei Zhang, Lei School of Computer Science Shaanxi Province Key Laboratory of Speech and Image Information Processing Northwestern Polytechnical University Xi'an China

ISBN: (纸本)9783642420566

Hyperspectral classification techniques are widely used for detailed analysis of the earth surface. However, mixed pixels caused by the relatively low spatial resolution of the imaging system are the big burden for traditional pure-pixel-hypothesis based hard classification methods. To address this problem, a novel method, which jointly uses soft classification and spectral unmixing, is proposed in this paper. The confusion matrix is exploited to determine the endmember set for each class. Then the generated endmember is adopted for spectral unmixing. The fractional abundance of training samples, which is generated from spectral unmixing, is utilized to optimize soft multinomial logistic regression classifier. The result of the optimized classifier will result in a more accurate confusion matrix. Thus, this procedure is executed iteratively to achieve required performance. Experimental results on synthetic and real hyperspectral data sets demonstrate the superiority of the proposed method for hyperspectral image classification. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Iterative methods

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Object Detector based on Enhanced Multi-scale Feature Fusion Pyramid Network 5

Object Detector based on Enhanced Multi-scale Feature Fusion...

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5th IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2021

作者： Zhao, Luan Zhang, Xiaofeng Nanchang Hangkong University Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition School of Information Engineering Nanchang China

Constructing the pyramidal architecture for the feature is currently a very effective way to obtain feature information of objects at different scales. Although the feature pyramid can realize the recognition and detection of multi-scale objects in the object detection task well, it still has some limitations. Since the feature information of different levels is often not from the same layer of the network, it is difficult to obtain the feature of different objects information at a certain scale from a certain level feature map of the pyramid network. To solve this problem, we present a novel object detection architecture, named Enhanced Multi-scale Feature Fusion Pyramid Network (EMFFPNet). Our network consists of Enhanced Multi-scale Feature Fusion Module (EMFFM) and Predictor Optimization Module (POM). In EMFFM, Features at different levels can be fused into the Enhanced features as outputs, which are more representative and deterministic. In order to enable the enhanced features to play their respective roles in the pyramid network, we assign different weights to fusion features of different levels in POM. We perform the experiments on the COCO detection benchmark. The experimental results indicate that the performance of our model is much better than the state-of-the-art model. © 2021 IEEE.

关键词： Object detection

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Research on state monitoring of bridge cable based on optical fiber sensing technology 21

Research on state monitoring of bridge cable based on optica...

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21st International Conference on Optical communications and Networks, ICOCN 2023

作者： Xu, Chunying Wu, Xinjie Liang, Ruixin Zhou, Yu Yang, Chengyu Wei, Chuliang College of Enineering Guangdong Province Shantou515013 China Guangdong Provincial Key Laboratory of Digital Signal and Image Processing China

ISBN: (纸本)9798350343502

In this paper, the strain and vibration of the bridge cable and its compensation device were monitored using fiber optic grating (FBG) sensing technology on the Zhoushan-Daishan Bridge in Zhoushan, Zhejiang province. During the monitoring period, the bridge experienced two typhoon events. The strain and vibration signals were analyzed. The results showed that the typhoon 'Muifa' had a greater impact on the Zhoushan-Daishan Bridge than typhoon 'Hinnamnor'. And there was no movement of the expansion compensation device during the monitoring period. © 2023 IEEE.

关键词： Vibration analysis

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