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检索条件"任意字段=5th International Conference on Pattern Recognition in Bioinformatics"

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5th international conference on Mining Intelligence and Knowledge Exploration, MIKE 2017

5th International Conference on Mining Intelligence and Know...

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5th international conference on Mining Intelligence and Knowledge Exploration, MIKE 2017

ISBN: (纸本)9783319719276

the proceedings contain 40 papers. the special focus in this conference is on Mining Intelligence and Knowledge Exploration. the topics include: Despeckling with structure preservation in clinical ultrasound images using historical edge information weighted regularizer;fingerprint image quality assessment and scoring;pattern based information retrieval approach to discover extremist information on the internet;improved community interaction through context based citation analysis;Portfolio optimization in dynamic environments using MemSPEAII;a multi-objective evolutionary algorithm for color image segmentation;Face recognition by RBF with wavelet, DCV and modified LBP operator face representation methods;DNN-HMM acoustic modeling for large vocabulary Telugu speech recognition;emotion recognition through facial gestures - a deep learning approach;memetic algorithm based on global-best harmony search and hill climbing for part of speech tagging;a study on crossmodal correspondence in sensory pathways through forced choice task and frequency based correlation in sound-symbolism;point process modeling of spectral peaks for low resource robust speech recognition;Significance of DNN-AM for multimodal sentiment analysis;a concept driven graph based approach for estimating the focus time of a document;query morphing: A proximity-based approach for data exploration and query reformulation;wikiSeeAlso: Suggesting tangentially related concepts (see also links) for wikipedia articles;integrating knowledge encoded by linguistic phenomena of Indian languages with neural machine translation;partitioned-based clustering approaches for single document extractive text summarization;Supervised approaches to assign cooperative patent classification (CPC) codes to patents;arousal prediction of news articles in social media;mining informative words from the tweets for detecting the resources during disaster.

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JOINT TRANSFORM CORRELATOR UTILIZING REWRITEABLE MAGNETOOPTIC COMPACT-DISKS AS INPUT SPATIAL LIGHT MODULATORS 5

JOINT TRANSFORM CORRELATOR UTILIZING REWRITEABLE MAGNETOOPTI...

引用

5th conference on Optical pattern recognition

作者： TAYLOR, TS JORDAN, DJ GREGORY, DA JUTAMULIA, S USA MISSILE COMMANDREDSTONE ARSENALAL 35898

ISBN: (纸本)0819415413

Commercially available rewritable magneto-optic compact disks are utilized as input spatial light modulators in a hybrid optical/digital joint transform correlator and in a purely optical correlator. Identical images are written on two disks using a commercially available optical disk drive, and good auto-correlation signals were obtained.

关键词： Joint transforms Optical correlators Magneto-optics Compact discs Hybrid optics Optical pattern recognition Cameras Optical discs Aluminum Ions

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DTW for Matching Radon Features: A pattern recognition and Retrieval Method

DTW for Matching Radon Features: A Pattern Recognition and R...

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13th international conference on Advanced Concepts for Intelligent Vision Systems (ACIVS) / 5th ACM/IEEE international conference on Distributed Smart Cameras (ICDSC)

作者： Santosh, K. C. Lamiroy, Bart Wendling, Laurent INRIA Nancy Grand Est Res Ctr LORIA Campus SciBP 239 F-54506 Vandoeuvre Les Nancy France Nancy Univ INPL LORIA F-54506 Nancy France Univ Paris 05 LIPADE F-75270 Nancy France

ISBN: (纸本)9783642236877

In this paper, we present a method for pattern such as graphical symbol and shape recognition and retrieval. It is basically based on dynamic programming for matching the Radon features. the key characteristic of the method is to use DTW algorithm to match corresponding pairs of histograms at every projecting angle. this allows to exploit the Radon property to include both boundary as internal structure of shapes, while avoiding compressing pattern representation into a single vector and thus miss information, thanks to the DTW. Experimental results show that the method is robust to distortion and degradation including affine transformations.

关键词： Radon Transform DTW pattern recognition and Retrieval

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Script line separation from Indian multi-script documents 5

Script line separation from Indian multi-script documents

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5th international conference on Document Analysis and recognition, ICDAR 1999

作者： Pal, U. Chaudhuri, B.B. Computer Vision and Pattern Recognition Unit Indian Statistical Institute 203 B. T. Road Calcutta35 India

ISBN: (纸本)0769503187

In a multi-lingual country like India, a document page may contain more than one script form. Under the three-language formula, the document may be printed in English, Devnagari and one of the other official Indian languages. For OCR of such a document page, it is necessary to separate these three script forms before feeding them to the OCRs of individual scripts. In this paper, an automatic technique of separating the text lines using script characteristics and shape based features is presented. At present, the system has an overall accuracy of about 98.5%. © 1999 IEEE.

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Optimization of Feature Selection in Face recognition System Using Differential Evolution and Genetic Algorithm 5th

Optimization of Feature Selection in Face Recognition System...

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5th international conference on Soft Computing for Problem Solving (SocProS)

作者： Maheshwari, Radhika Kumar, Manoj Kumar, Sushil Amity Univ Amity Sch Engn & Technol Dept Comp Sci & Engn Noida 201313 Uttar Pradesh India

ISBN: (纸本)9789811004513;9789811004506

this paper compares the results of the optimization techniques for feature selection of face recognition system in which face as a biometric template gives a large domain of features for optimizing feature selection. We attempt to minimize the number of features necessary for recognition while increasing the recognition accuracy. It presents the application of differential evolution and genetic algorithm for feature subset selection. We are using local directional pattern (LDP), an extended approach of local binary patterns (LBP), to extract features. then, the results of DE and GA are compared with the help of an extension of support vector machine (SVM) which works for multiple classes. It is used for classification. the work is performed on 10 images of ORL database resulting in better performance of differential evolution.

关键词： Face recognition system Differential evolution Local directional pattern (LDP) Multi-support vector machine (m-SVM) Genetic algorithm Feature selection

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Research on the Stability of pattern recognition Collaborative Algorithms Based on Data Mining 5

Research on the Stability of Pattern Recognition Collaborati...

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5th international conference on Computers, Information Processing and Advanced Education, CIPAE 2024

作者： Fan, Xue College of Computer Science and Technology Jilin University Changchun China

ISBN: (纸本)9798331527662

the contemporary era and world of big data has seen the stability of advanced pattern recognition and collaborative algorithms that are critical in the practical process of data mining. this research study primarily delves into the factors that significantly enhance algorithms' stability and optimized function. this factor is focused on ensuring reliable and consistent recognition models and patterns. Based on this context, this research primarily focuses on including data mining techniques to bolster collaborative algorithms' optimized functions and robustness. through a comprehensive analysis of a myriad of data sets, factors that significantly influence the stability of these algorithms are underscored. Findings, therefore, indicate that incorporating pattern recognition and collaborative algorithms based on data mining significantly improves the algorithmic stability of a system. thus, the research findings validate the extensive and empirical simulation and tests that efficiently maintain stability in a pattern recognition model. © 2024 IEEE.

关键词： Artificial Intelligence Attention Mechanism Collaborative Algorithms Data Mining Stability pattern recognition

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Efficient English Text Comprehension and pattern Understanding Model with ChatGPT 5

Efficient English Text Comprehension and Pattern Understandi...

引用

5th international conference on Sustainable Communication Networks and Application, ICSCNA 2024

作者： Lin, Wei Chengdu Technological University School of Foreign Languages and International Education Sichuan Chengdu611730 China

ISBN: (纸本)9798331530013

In the context of intelligent information system models, in order to further promote the development of natural language processing and explore its application scenarios in different fields, this study studied the English text understanding and pattern recognition model based on ChatGPT middleware from the modeling and analysis level. the model proposed in this study integrates the information of text and audio input as the modeling of multi-modal semantic understanding to improve the accuracy and universality of machine language understanding in complex environments. In order to transform human natural language into structured data and hierarchy that can be understood by machines, this study first explored the significance of natural language processing and the processing challenges in real applications. Subsequently, this study gave an in-depth explanation of the design and methods of the model, focusing on the key role of improving ChatGPT middleware in simplifying the modal fusion process and thus ensuring the accuracy and applicability of the output results. In the experimental verification part, this study used a variety of self-collected data sets to evaluate the model. the experimental results show that the proposed model has an accuracy of 97.5% for text semantic understanding, an accuracy of 98.2% for pattern recognition tasks, and an overall accuracy of 99.2%. Compared with traditional algorithms, proposed model has better comprehensive performance. © 2024 IEEE.

关键词： Middleware

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Kernel methods for exploratory pattern analysis: A demonstration on text data

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10th international Symposium on Structural and Syntactic pattern recognition/5th international conference on Statistical Techniques in pattern recognition

作者： De Bie, T Cristianini, N Katholieke Univ Leuven ESAT SCD B-3001 Heverlee Belgium Univ Calif Davis Dept Stat Davis CA 95616 USA

ISBN: (纸本)3540225706

Kernel Methods are a class of algorithms for pattern analysis with a number of convenient features. they can deal in a uniform way with a multitude of data types and can be used to detect many types of relations in data. Importantly for applications, they have a modular structure, in that any kernel function can be used with any kernel-based algorithm. this means that customized solutions can be easily developed from a standard library of kernels and algorithms. this paper demonstrates a case study in which many algorithms and kernels are mixed and matched, for a cross-language text analysis task. All the software is available online.

关键词： Artificial intelligence

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5th international conference on Soft Computing as Transdisciplinary Science and Technology, CSTST '08 - Proceedings

5th International Conference on Soft Computing as Transdisci...

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5th international conference on Soft Computing As Transdisciplinary Science and Technology, CSTST '08

ISBN: (纸本)9781605580463

the proceedings contain 111 papers. the topics discussed include: evolutionary multiobjective optimization and multiobjective fuzzy system design;chance discovery as value sensing by data based meta cognition;building classification rules for case based classifier using fuzzy sets and formal concept analysis;intelligent hybrid system for pattern recognition and classification;hybrid approach using ant colony optimization and fuzzy logic to solve multi-criteria hybrid flow shop scheduling problem;improving performance of intrusion detection system by applying a new machine learning strategy;network security simulation and evaluation;extending web applications with a lightweight zero knowledge proof authentication;implementation of a neural-based navigation approach on indoor and outdoor mobile robots;a human-machine interface design for direct rehabilitation using a rehabilitation robot;and Persian on-line handwritten character recognition by RCE spatio-temporal neural network.

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Design and implementation of modern elevator group control system

Design and implementation of modern elevator group control s...

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5th international conference on Machine Learning and Cybernetics

作者： Chen, Zhi-Ming Luo, Fei Xu, Yu-Ge Cao, Jian-Zhong South China Univ Technol Coll Automat Sci & Engn Guangzhou 510640 Guangdong Peoples R China

ISBN: (纸本)1424400600

the design and implementation of a modern elevator group control system (EGCS) is introduced in this paper. the basic considerations of designing an EGCS are discussed, including related system parameters, evaluation criterions and traffic patterns. Least squares support vector machine algorithm is employed for traffic prediction. Using multi-support vector machine, the traffic pattern recognition is accomplished, then based on that recognition, the control strategies are generated. In the hall call assignment, the re-scheduling ability is achieved by the elevator suitability re-evaluation mechanism. A comparison with an older model demonstrates the effectiveness of the proposed EGCS.

关键词： elevator group control system traffic prediction traffic pattern recognition support vector machine hall call assignment

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