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international conference on BioMedical Engineering and Informatics (BMEI)

作者： Qiong Xu Xuanqin Mou Institute of Image Processing and Pattern Recognition Xi' an Jiaotong University Xi'an Shaanxi China

Interior tomography is to reconstruct the interior region of interest (ROI) from the projection data just across the ROI. One kind of interior reconstruction methods is based on the inversion of truncated Hilbert transform (thT) when there is a known sub-region inside ROI. However, the result via this method is usually to be degraded by noise in real data case. In this paper, we propose to incorporate the total variation (TV) minimization constraint into the thT-based interior tomography to improve the reconstruction quality. therein, we first carry out projection-on-convex-sets (POCS) iteration on each chord, and then we perform a soft-threshold based TV minimization on the intermediate image. In order to validate the proposed method, we conduct both simulated and real data experiments. the results show that with TV constraint the proposed method can lead to better ROI with less noise.

关键词： TV Image reconstruction Minimization Transforms Noise Computed tomography

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Evolving Ensemble of Classifiers In Low-Dimensional Spaces Using Multi-Objective Evolutionary Approach

Evolving Ensemble of Classifiers In Low-Dimensional Spaces U...

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international conference on Computer and Information Science (ACIS)

作者： Kushan Ahmadian Abbas Golestani Morteza Analoui Mohammad R. Jahed Iran

In this paper we discuss a new strategy to create ensemble of classifiers based on the multi objective evolutionary optimization. Instead of using feature selection technique which has been widely used in multi objective evolutionary approaches for ensemble generating, we have used a bagging-and-boosting-like strategy which also covers problems with lower dimensional feature spaces in which using feature selection technique may lead to ambiguous subspaces. After creating classifiers based on the amount of error created for each class, a multi-objective genetic algorithm has used to combine them to provide a set of powerful ensembles. Comprehensive experiments demonstrate the effectiveness of the proposed strategy.

关键词： Optimization methods Bagging Boosting Pareto optimization Genetic algorithms Design optimization pattern recognition Supervised learning Neural networks Error analysis

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A Robust pitch estimation approach for clean speech

A Robust pitch estimation approach for clean speech

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international conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)

作者： Mohamed Anouar Ben Messaoud Aïcha Bouzid Noureddine Ellouze Signal Image and Pattern Recognition Laboratory Faculty of Sciences of Tunis Tunis Tunisia

In this work, we present an algorithm for estimating the fundamental frequency in speech signals. Our approach is based on the spectral compression by the autocorrelation of the speech multi-scale product analysis. It consists of operating the product of compressed copies of the original spectrum on the multi-scale product autocorrelation. the multi-scale product is based on making the product of the speech wavelet transform coefficients at three successive dyadic scales. the wavelet used is the quadratic spline function with a support of 0.8 ms. We estimate the pitch for each time frame based on its multi-scale product autocorrelation of the harmonic product spectrum structure. We evaluate our approach on the Keele database. Experimental results show the effectiveness of our method presenting a good performance surpassing the other algorithms.

关键词： Speech Wavelet transforms Estimation Correlation Algorithm design and analysis Harmonic analysis

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Study on the Method of Image Restoration in the Environment of Dust

Study on the Method of Image Restoration in the Environment ...

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international conference on Wireless Communications, Networking and Mobile Computing (WiCom)

作者： Yuanyu Wang Yuanzong Li Tianxu Zhang Department of Computer Fundamental Education Taiyuan University Of Technology Taiyuan China College of Mechanical Engineering Taiyuan University Of Technology Taiyuan China Institute of Pattern Recognition and A.I State Key Laboratory of Image Processing and Intelligent Control HuaZhong University of Science and Technology Wuhan China

In order to solve the problem of image degradation caused by dust environments, an image degradation model considering multiple scattering factors caused by dust was first established using the first-order multiple scattering method. then, a dark channel prior principle was applied to present an image restoration algorithm based on the image degradation model. Finally, GA optimization algorithm was applied to optimize the atmospheric light and the exposure parameters. this optimization algorithm was established according to the criterion of the image evaluation based on kirsch operator with automatic threshold. By using the method an optimistic result of image restoration was obtained. the experimental results have shown that the method not only enhanced luminance and contrast, but also discovered more detail edges information. the method provided a foundation for target recognition in the dust environments.

关键词： Image edge detection Image restoration Scattering Degradation Gallium Atmospheric modeling Genetic algorithms

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HAWAII international conference ON SYSTEM SCIENCES, 6th, PROCEEDINGS, 1973.

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1973年

作者： Fine, Terrence L. Ruspini, Enrique H. Butler, G.A. Ritea, H.B. Michalopoulos, Demetrios A. Lopez-Toledo, Alejandro A. Jain, Anil K. Chandrasekaran, B. Gose, Earl E. Wu, Francis B.H.

Following is a continuation of the list of titles and authors: Approach to pattern Classification When Little Is Known. By Terrence L. Fine. Fast method for probabilistic and Fuzzy Cluster Analysis Using Association Measures. By Enrique H. Ruspini. Estimation of the Information in a Two Class Sample. By G. A. Butler and H. B. Ritea. Non-Parametric Method with Applications to pattern recognition and Mode Estimation. By Demetrios A. Michalopoulos. On the Estimation of the Inverse of a Covariance Matrix. By Alejandro A. Lopez-Toledo. Conditions for Perfect Discrimination for Independent Measurements. By Anil K. Jain and B. Chandrasekaran. Some Second-Order Techniques for Selecting Subsets of pattern recognition Properties. By Earl E. Gose and Francis B. H. Wu.

关键词： Systems science and cybernetics

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EMG pattern recognition using decomposition techniques for constructing multiclass classifiers

EMG pattern recognition using decomposition techniques for c...

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IEEE/RAS-EMBS international conference on Biomedical Robotics and Biomechatronics (BioRob)

作者： Huaiqi Huang Tao Li Claudio Bruschini Christian Enz Volker M. Koch Jörn Justiz Christian Antfolk BME Lab Bern University of Applied Sciences Biel Switzerland Ecole Polytechnique Fédérale de Lausanne (EPFL) Integrated Circuits Laboratory Neuchâtel Switzerland Department of Biomedical Engineering Lund University Lund Sweden

ISBN: (纸本)9781509032884

To improve the dexterity of multi-functional myoelectric prosthetic hand, more accurate hand gesture recognition based on surface electromyographic (sEMG) signal is needed. this paper evaluates two types of time-domain EMG features, one independent feature and one combined feature including four features. the selected features from eight subjects with 13 finger movements were tested with four decomposed multi-class support vector machines (SVM), four decomposed linear discriminant analyses (LDA) and a multi-class LDA. the classification accuracy, training, and classification time are compared. the results have shown that the combined features decrease error rate, and binary tree based decomposition multiclass classifiers yield the highest classification success rate (88.2%) with relatively low training and classification time.

关键词： Support vector machines Electromyography Training Electrodes Kernel Prosthetics Muscles

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CEP-Based SLO Evaluation 1

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6th European conference on Service-Oriented and Cloud Computing, ESOCC 2017

作者： Kritikos, Kyriakos Zeginis, Chrysostomos Paravoliasis, Andreas Plexousakis, Dimitris Institute of Computer Science - FORTH Heraklion Greece Computer Science Department University of Crete Heraklion Greece

ISBN: (数字)9783319790909

ISBN: (纸本)9783319790893

Modern service-based applications (SBAs) operate in highly dynamic environments where both underlying resources and the application demand can be constantly changing which external SBA components might fail. thus, they need to be rapidly modified to address such changes. Such a rapid updating should be performed across multiple levels to better deal, in an orchestrated and globally-consistent manner, with the current problematic situation. First of all, this means that a fast and scalable event generation and detection mechanism should exist to rapidly trigger the adaptation workflow to be performed. Such a mechanism needs to handle all kinds of events occurring at different abstraction levels and to compose them so as to detect more advanced situations. To this end, this paper introduces a new complex event processing framework able to realise the respective features mentioned (processing speed, scalability) and have the flexibility to capture and sense any kind of event or event combination occurring in the SBA system. Such a framework is wrapped in the form of a REST service enabling to manage the event patterns that need to be rapidly detected. It is also well connected to other main components of the SBA management system, via a publish-subscribe mechanism, including monitoring and the adaptation engines. © 2018, Springer international Publishing AG, part of Springer Nature.

关键词： pattern recognition

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Understanding Event Boundaries for Egocentric Activity recognition from Photo-Streams 25th

Understanding Event Boundaries for Egocentric Activity Recog...

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25th international conference on pattern recognition Workshops, ICPR 2020

作者： Cartas, Alejandro Talavera, Estefania Radeva, Petia Dimiccoli, Mariella Faculty of Mathematics and Computer Science University of Barcelona Gran Via de les Corts Catalanes 585 Barcelona08007 Spain Bernoulli Institute University of Groningen Nijenborgh 9 Groningen9747 AG Netherlands C/ Llorens i Artigas 4-6 Barcelona08028 Spain

ISBN: (纸本)9783030687953

the recognition of human activities captured by a wearable photo-camera is especially suited for understanding the behavior of a person. However, it has received comparatively little attention with respect to activity recognition from fixed cameras. In this work, we propose to use segmented events from photo-streams as temporal boundaries to improve the performance of activity recognition. Furthermore, we robustly measure its effectiveness when images of the evaluated person have been seen during training, and when the person is completely unknown during testing. Experimental results show that leveraging temporal boundary information on pictures of seen people improves all classification metrics, particularly it improves the classification accuracy up to 85.73%. © 2021, Springer Nature Switzerland AG.

关键词： Cameras

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Over-the-Air Radar Emitter Signal Classification Based on SDR

Over-the-Air Radar Emitter Signal Classification Based on SD...

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6th international conference on Intelligent Computing and Signal Processing (ICSP)

作者： Yan Xia Zhiyuan Ma Zhi Huang School of Electronic Engineering Naval University of Engineering Wuhan China

ISBN: (纸本)9781665447300

At present, in the field of radar emitter classification, theoretical simulation is mostly used to carry out algorithm research. However, there are few schemes to study signal classification in real electromagnetic environment using actual hardware. therefore, this paper proposes a radar emitter classification scheme based on HackRF Software Defined Radio (SDR) and deep learning to solve the problem of weak engineering practice. Firstly, the GNU Radio development environment is used to realize the integration design of real space signal transceiver and time-frequency analysis algorithm application on HackRF hardware platform. then, a classification model with 11 layers network is constructed to automatically extract the deep features of intra-pulse signal time-frequency image. Finally, the classification performance of eight kinds of signals in real electromagnetic environment is tested. the total recognition accuracy of this scheme is more than 83% under 6dB low Signal-to-Noise Ratio (SNR), which proves the effectiveness of the scheme, and provides an important basis for practical engineering application in the future.

关键词： Time-frequency analysis Spaceborne radar Software algorithms pattern classification Feature extraction Hardware Radar signal processing

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Classification method of images based on composition and its application to image retrieval

International Conference on Multimedia Computing and Systems...

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international conference on Multimedia Computing and Systems -Proceedings 1999年 2卷 240-244页

作者： Maeda, Shigenori Mukunoki, Masayuki Ikeda, Katsuo Kyoto Univ Kyoto Japan

We propose a visual query method for image retrieval, in which the user expresses the composition of the target image by selecting one of the composition types presented by the system, and also propose an image classification method to derive composition types from an image database. From the viewpoint of communication between the system and its user, we point out the problem of visual query methods using concrete images as queries. though suited to convey visual image properties, they grow the ambiguity in the system's interpretation of queries. To manage this tradeoff, we implemented our methods in a prototype system and derived composition types from an image database to show how our query method works in image retrieval.

关键词： pattern recognition

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