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检索条件"任意字段=Proceedings of the 2023 12th International Conference on Computing and Pattern Recognition"

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Functional mesh learning for pattern analysis of cognitive processes

Functional mesh learning for pattern analysis of cognitive p...

引用

12th IEEE international conference on Cognitive Informatics and Cognitive computing, ICCI*CC 2013

作者： Firat, Orhan Özay, Mete Önal, Itir Oztekin, Ilke Vural, Fatoş T. Yarman Department of Computer Engineering Middle East Technical University Ankara Turkey Department of Psychology Koç University Istanbul Turkey

ISBN: (纸本)9781479907816

We propose a statistical learning model for classifying cognitive processes based on distributed patterns of neural activation in the brain, acquired via functional magnetic resonance imaging (fMRI). In the proposed learning machine, local meshes are formed around each voxel. the distance between voxels in the mesh is determined by using functional neighborhood concept. In order to define functional neighborhood, the similarities between the time series recorded for voxels are measured and functional connectivity matrices are constructed. then, the local mesh for each voxel is formed by including the functionally closest neighboring voxels in the mesh. the relationship between the voxels within a mesh is estimated by using a linear regression model. these relationship vectors, called Functional Connectivity aware Local Relational Features (FC-LRF) are then used to train a statistical learning machine. the proposed method was tested on a recognition memory experiment, including data pertaining to encoding and retrieval of words belonging to ten different semantic categories. Two popular classifiers, namely k-Nearest Neighbor and Support Vector Machine, are trained in order to predict the semantic category of the item being retrieved, based on activation patterns during encoding. the classification performance of the Functional Mesh Learning model, which range in 62-68% is superior to the classical multi-voxel pattern analysis (MVPA) methods, which range in 40-48%, for ten semantic categories. © 2013 IEEE.

关键词： Encoding (symbols)

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An Adaptive Sliding-mode Controller for Flexible-joint Manipulator 12

An Adaptive Sliding-mode Controller for Flexible-joint Manip...

引用

12th IEEE international conference on Control, Automation and Information Sciences, ICCAIS 2023

作者： Chiem, Nguyen Xuan Pham, thuy Xuan thai, Pham Duy Phan, Tran Cong Le Quy Don Technical University Department of Automation and Computing Techniques Hanoi Viet Nam

ISBN: (纸本)9798350328783

this paper represents a method of designing adaptive sliding mode control law for a class of flexible joint manipulators. the method aims at developing and deploying a controller for the system in case of existing disturbances in the process of generating control signal for the actuator. For drivers and motors in low-cost flexible-joint manipulator systems, there are always frictions and torque deviations when they operate. the proposed controller is designed to eliminate the impact of such disturbances on the tracking performance of the manipulator. To validate the design method, the stability of the control law is examined by using Lyapunov method. the performance is evaluated by simulation results as well as real-time responses of the custom-developed system;in addition, they are compared to ones from the counterparts. © 2023 IEEE.

关键词： Lyapunov methods

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Application of Python Scientific computing library and Simulation in Circuit Analysis 12

Application of Python Scientific computing library and Simul...

引用

12th IEEE international conference on Communication Systems and Network Technologies, CSNT 2023

作者： Zhang, Hong Yang, Ping Niu, Yali Beijing Polytechnic Beijing China

ISBN: (纸本)9781665462617

Complicated manual calculation and drawing often appear in circuit analysis, which brings difficulty to circuit analysis. Manual ways to analysis of the circuit is timeconsuming and laborious, and prone to errors. Python can solve the problem better in circuit analysis instead of manual ways. Python is a high-level, general-purpose interpreted programming language that is widely used in scientific computing and engineering. It also includes a vast collection of Python packages for scientific computing. this ecosystem of scientifically oriented libraries ranges from generic core libraries- such as NumPy, SciPy, and Matplotlib -to more specific libraries for particular problem domains [1]. 1So Python has many applications in circuit analysis, such as equation solving, curve drawing, logic calculation and so on. In this paper, we apply Sympy library of Python to solve the equations of branch current method, use Matplotlib library to draw the sinusoidal AC signal curve, and use programming language of Python to realize the design of logic which is also the realization of logic functions. With the rapid development of computer technology, the application of new technology and software tools in circuit analysis will greatly improve the efficiency of circuit analysis. © 2023 IEEE.

关键词： Python

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proceedings - 2019 IEEE international conference on Cloud computing, CLOUD 2019 - Part of the 2019 IEEE World Congress on Services

Proceedings - 2019 IEEE International Conference on Cloud Co...

引用

12th IEEE international conference on Cloud computing, CLOUD 2019

ISBN: (纸本)9781728127057

the proceedings contain 84 papers. the topics discussed include: data protection as a service in the multi-cloud environment;robust management of trans-cloud applications;an adaptive approach for dealing with flow disruption in virtualized water-cooled data centers;cloud VM provisioning using analytical performance models;QuADD : quantifying accelerator disaggregated datacenter efficiency;TrIMS: transparent and isolated model sharing for low latency deep learning inference in function-as-a-service;STRETCH: in-memory storage with autoscaling for cluster computing;exploiting serverless runtimes for large-scale optimization;and non-intrusive cloud application transaction pattern discovery.

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Gender-Aware Speech Emotion recognition in Multiple Languages 12th

Gender-Aware Speech Emotion Recognition in Multiple Language...

引用

12th international conference on pattern recognition Applications and Methods (ICPRAM)

作者： Nicolini, Marco Ntalampiras, Stavros Univ Milan Dept Comp Sci Milan Italy

ISBN: (纸本)9783031547256;9783031547263

this article presents a solution for Speech Emotion recognition (SER) in multilingual setting using a hierarchical approach. the approach involves two levels, the first level identifies the gender of the speaker, while the second level predicts their emotional state. We evaluate the performance of three classifiers of increasing complexity: k-NN, transfer learning based on YAMNet, and Bidirectional Long Short-Term Memory neural networks. the models were trained, validated, and tested on a dataset that includes the big-six emotions and was collected from well-known SER datasets representing six different languages. Our results indicate that there are differences in classification accuracy when considering all data versus only female or male data, across all classifiers. Interestingly, prior knowledge of the speaker's gender can improve the overall classification performance.

关键词： Audio pattern recognition Machine learning Transfer learning Convolutional neural network YAMNet Multilingual speech emotion recognition

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Categorical Boosting Machine for Tamil Character recognition Using Shape Based Features 7

Categorical Boosting Machine for Tamil Character Recognition...

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2023 7th international conference On computing, Communication, Control And Automation, ICCUBEA 2023

作者： T.m, Vishnu Mukundan Nevatia, Isha Mishra, Tusar Kanti School of Computer Science & Engineering Vellore Institute of Technology Vellore India

ISBN: (纸本)9798350304268

Tamil is one of the world's earliest surviving languages, from which modern Indian scripts draw inspiration. However, there has been limited development of Optical Character recognition techniques for Tamil characters. this paper describes a model for Tamil vowels-based Optical Character recognition. the strategy seeks to utilise a CHFR feature extraction technique to extract three distinct feature vectors from the contours of each individual character's centroid. these feature vectors are condensed into a single vector before being sent to the CatBoost classifier for classification. Using the Optuna framework, hyperparameter optimisation and comparative analysis of existing models are performed. the proposed scheme is applied to a dataset of 6,972 handwritten samples evenly divided into 12 classes representing the vowels of the Tamil alphabet. the primary evaluation metric is accuracy, and 84.36% testing accuracy is observed. © 2023 IEEE.

关键词： CatBoost CHFR feature extraction handwritten character recognition OCR pattern recognition Tamil characters

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Advanced Research in Applied Artificial Intelligence 2012

引用

丛书名： Lecture Notes in Computer Science

2012年

作者： He Jiang Wei Ding Moonis Ali Xindong Wu

ISBN: (数字)9783642310874

ISBN: (纸本)9783642310867

this volume constitutes the thoroughly refereed conference proceedings of the 25th international conference on Industrial Engineering and Other Applications of Applied Intelligend Systems, IEA/AIE 2012, held in Dalian, China, in June 2012. the total of 82 papers selected for the proceedings were carefully reviewed and selected from numerous submissions. the papers are organized in topical sections on machine learning methods; cyber-physical system for intelligent transportation applications; AI applications; evolutionary algorithms, combinatorial optimization; modeling and support of cognitive and affective human processes; natural language processing and its applications; social network and its applications; mission-critical applications and case studies of intelligent systems; AI methods; sentiment analysis for asian languages; aspects on cognitive computing and intelligent interaction; spatio-temporal datamining, structured learning and their applications; decision making and knowledge based systems; pattern recognition; agent based systems; decision making techniques and innovative knowledge management; machine learning applications.

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A Novel Iris Segmentation Approach Using Spindle Ternary Tree 12

A Novel Iris Segmentation Approach Using Spindle Ternary Tre...

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12th international conference on Information Technology in Medicine and Education, ITME 2022

作者： Lin, Yuhui Ye, Zubin Xiao, Baosen Fuzhou Institute of Technology School of Computing and Information Science Fuzhou China Xiamen University Tan Kah Kee College School of Information Science and Technology Zhangzhou China

ISBN: (纸本)9798350310153

this paper presents an accurate and novel iris segmentation approach. First rough iris region is extracted by boosted Local Binary pattern features classifier. Follow Intensity gradient matrix is then built though gray gradient operator under polar coordinate. then Special Ternary Tree model is proposed to handle the matrix for tracking iris boundaries by searching the best route as iris boundary. Comparatively, experimental results on the popular iris databases demonstrate that the proposed approach is accurate, efficient and robust. © 2022 IEEE.

关键词： Local binary pattern

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Scale-adaptive feature points extraction and dual-scale based high-precision image registration

Scale-adaptive feature points extraction and dual-scale base...

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2012 IEEE 12th international conference on Computer and Information Technology, CIT 2012

作者： Gao, Zunqi Ming, Delie Xiao, Liping Wang, Hai Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China National Laboratory of Aerospace Intelligence Control Technology Beijing Aerospace Automatic Control Institute Beijing China Department of Computer Science and Engineering Pohang University of Science and Technology Pohang Korea Republic of

ISBN: (纸本)9780769548586

the SIFT algorithm had a profound impact on the area of image local feature extraction and computer vision, since its inception. Because of its robustness and anti-interference performance, it has been widely applied in engineering. However, in practical usage of SIFT, there are actually no sufficient feature points that can be extracted to perform the image registration. For tiny scale targets, this situation becomes even worse. Based on the analysis of the scale-space, this paper puts forward a scale-adaptive feature points extraction method (SFPE). SFPE can extract more feature points than traditional SIFT algorithm, especially when the target scale is tiny. Furthermore, a dual-scale based high-precision image registration process (DHIR) is proposed in this paper. In DHIR, a small-scale matching (precise matching) process is performed after the large-scale registration. Experimental results show that the DHIR is more effective to eliminate mismatches than traditional SIFT algorithm. © 2012 IEEE.

关键词： Feature extraction

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A new multi-pattern matching algorithm based on frequently used group

A new multi-pattern matching algorithm based on frequently u...

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2012 IEEE 12th international conference on Computer and Information Technology, CIT 2012

作者： Yang, Guangming Li, Shuang Tan, Zhenhua Yan, Xiangshuai Hou, Xiangjun Software College Northeastern University Shenyang China

ISBN: (纸本)9780769548586

Along with the rapid development of computer technology, people's lives are increasingly dependent on computers. At the same time, the computer system is facing increasingly complex and diverse sabotage and attacks. Destruction of computer viruses is most widespread and severe among them, so studying anti-virus technology is imminent. Virus scanning engine is the kernel of anti-virus software, it uses signature database to identify known viruses. the pattern matching algorithm is the core algorithm of the entire anti-virus software. this paper first introduces some background knowledge of anti-virus software, pattern matching algorithm and hash algorithm. then it proposes a new type of multi-pattern matching algorithm with automata based on frequently matching hash values. Combining the advantages of fast calculation of hash function and parallel pattern matching of automata, it has significant performance advantages in the circumstance of virus signature matching. It can also be applied to other similar circumstances after making a little improvement, such as gene sequence alignment where patterns are also very long. © 2012 IEEE.

关键词： pattern matching

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