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Energy, Power and Grid (ICEPG), international conference on

作者： Yang Liu Shifang He Shiyi Chen Weiguo Zu Department of China Yangtze Power Co. Ltd. Yichang Xiling Road 1 Hubei China

ISBN: (数字)9798350377798

ISBN: (纸本)9798350377804

With advancements in machine learning, automated pattern recognition has significantly improved various fields, especially in power systems. Accurate and rapid identification of partial discharge (PD) types in transformers is vital for system stability and safety. this paper presents a novel method for transformer PD pattern recognition based on optimized convolutional neural networks (CNN) and phase-resolved partial discharge (PRPD) pattern. the approach involves creating a PRPD dataset from ultra-high-frequency (UHF) sensor signals, followed by data preprocessing and labeling. By optimizing the CNN’s network structure and hyperparameters, the method achieves a remarkable recognition accuracy of $99.8 \%$, outperforming traditional algorithms like Support Vector Machines (SVM) ($\mathbf{9 3. 7 \%)}$ and Random Forests (RF) (89.3%). this study demonstrates the superior engineering applicability of the proposed method, highlighting the importance of network layer depth, convolutional kernel size, and activation function selection in improving model performance and generalization.

关键词： Support vector machines Partial discharges Adaptation models Accuracy Power system stability Transformers Stability analysis pattern recognition Convolutional neural networks Monitoring

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Matching Local Invariant Features: How Can Contextual Information Help?

Matching Local Invariant Features: How Can Contextual Inform...

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international conference on Systems, Signals and Image Processing, IWSSIP

作者： Desire Sidibe Philippe Montesinos Stefan Janaqi LGI2P-Ecole des Mines Ales Parc scientifique Georges Besse Nimes France

Local invariant features are a powerful tool for finding correspondences between images since they are robust to cluttered background, occlusion and viewpoint changes. However, they suffer the lack of global information and fail to resolve ambiguities that can occur when an image has multiple similar regions. Considering some global information will clearly help to achieve better performances. the question is which information to use and how to use it. While previous approaches use context for description, this paper shows that better results are obtained if contextual information is included in the matching process. We compare two different methods which use context for matching and experiments show that a relaxation based approach gives better results.

关键词： Shape Robustness Image resolution Image matching pattern matching Layout Image retrieval Image registration Robots Object recognition

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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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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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Equalized orthogonal map-based DNA microarray data analysis for cancer diagnosis

Equalized orthogonal map-based DNA microarray data analysis ...

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international conference on Information, Communications and Signal Processing

作者： Jagdish C. Patra Sineepong Detpongsante Pramod K. Meher Ee Luang Ang School of Computer Engineering Nanyang Technological University Singapore

ISBN: (纸本)9781424409822;1424409829

A new approach to cancer diagnosis involves the analysis of gene expression data. However, to make sense of multidimensional DNA microarray data is a challenging task. Beyond 3 dimensions, it is very difficult for humans to make intuitive interpretation of how each data point is distributed, how they are interrelated, and how they should be categorized. Equalized orthogonal map (EOM), an approach to dimension reduction was able to produce topologically correct mappings for visualization and classification of cancer types. Performance comparison with a self-organizing map (SOM) is also discussed. Experimental results show that EOM performs well with DNA microarray data classification.

关键词： Cancer DNA Data analysis Data visualization Principal component analysis Topology Medical treatment pattern recognition Gene expression Multidimensional systems

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Research on Action pattern recognition Based on DeepConvLSTM

Research on Action Pattern Recognition Based on DeepConvLSTM

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international conference on Information Systems and Computer Aided Education (ICISCAE)

作者： Pengkai Guo Zhuo Li Yiyan Sun School of Artificial Intelligence and Automation Hohai University Nanjing China College of Energy and Electrical Engineering Hohai University Nanjing China

pattern recognition is an important way to improve the quality of life and promote scientific research. through the big data captured by the three-axis sensor, this paper focuses on the establishment of relevant models for the accurate classification of 19 motion modes , and analyses of the generalization ability and overfitting. this paper establishes DeepConvLSTM model by combining the original deep learning convolutional neural network (CNN) and long- term short-term memory recursion (LSTM). the model code about DeepConvLSTM was written by Python and relevant data was imported. In terms of methods, this paper evaluates the generalization ability of the model by using setaside method and K-fold cross-validation method respectively from the algorithm level. In terms of indicators, this paper selects accuracy, accuracy rate, recall rate and F1 value. Finally, the conclusion is drawn as follows: when epoch increases to 40, Train loss and Val loss basically fall together, indicating that the accuracy and stability of the model are *** paper use logistic regression model to solve the classification problem of human behavior. It is found that the classification effect of DeepConvLSTM model was better than that of LR model with higher accuracy and no overfitting phenomenon. in addition, Recall is used to analyze the sensitivity of the model. After several tests, it is found that the model shows good sensitivity and stability when the training times reaches 60. On this basis, considering the cost and efficiency of training comprehensively, the number of training is set as 60 in this paper, and the sensitivity and robustness of the model are both good. In conclusion, this paper establishes a scientific action pattern recognition model according to the conditions of the subject and the data given. the model is simple and easy to popularize. After verification and analysis, the model in this paper has strong accuracy, robustness and sensitivity, and has certain pra

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Interior tomography using the truncated Hilbert transform with the total variation constraint

Interior tomography using the truncated Hilbert transform wi...

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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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Rule-Based Approaches for Equivalence Checking of SpecC Programs

Rule-Based Approaches for Equivalence Checking of SpecC Prog...

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ACM and IEEE international conference on Formal Methods and Models for Co-Design (MEMOCODE)

作者： Subash Shankar Masahiro Fujita CUNY City University of New York NY USA University of Tokyo Tokyo Japan

this paper describes a rule-based approach for equivalence checking of reactive systems. the approach is based on new types of dependence and flow graphs that are more appropriate for reactive languages than traditional notions intended for transformational languages. Equivalence rules utilizing this static dependence and flow information are derived from language semantics. the rules are then applied in a bottom-up fashion, corresponding to the structures of the programs being checked, until equivalence is shown. A prototype toolset has been implemented, and results indicate speedups of several orders of magnitude over more traditional equivalence checkers. the paper describes our approach and tools, and also outlines how our methods can be used in a general equivalence checking system.

关键词： Prototypes Embedded system Software engineering Hardware Cities and towns Flow graphs System-level design Control system synthesis System-on-a-chip pattern recognition

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