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检索条件"任意字段=International Conference of Soft Computing and Pattern Recognition"

共 7533 条记录，以下是4931-4940 订阅

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Hybrid systems-a key to intelligent pattern recognition

Hybrid systems-a key to intelligent pattern recognition

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international Joint conference on Neural Networks (IJCNN)

作者： L. Kanal S. Raghavan Computer Science Department University of Maryland College Park MD USA LNK Corporation Inc. Riverdale MD USA

For the solution of complex problems in pattern recognition and more generally in machine intelligence, involving heterogeneous data sources of both numeric and symbolic information, the fundamental design philosophy is to employ hybrid methodologies rather than attempting to produce the solution using a single paradigm. The authors discuss some of the key issues which need to be addressed in integrating heterogeneous methodologies for intelligent solution of pattern recognition problems and some of the design principles found useful. They also describe some proof-of-concept systems developed at LNK Corporation. These systems include an automatic feature extraction and a target recognition system which combines heterogeneous technologies such as neural network paradigms, uncertainty calculi and expert systems, and heterogeneous data sources including optical and synthetic aperture radar and terrain databases.< >

关键词： Hybrid intelligent systems pattern recognition Machine intelligence Feature extraction Target recognition Neural networks Uncertainty Expert systems Adaptive optics Optical computing

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Support vector machine with orthogonal Chebyshev kernel

Support vector machine with orthogonal Chebyshev kernel

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international conference on pattern recognition

作者： Ning Ye Ruixiang Sun Yingan Liu Lin Cao College of Information and Technology Nanjing Forestry University Nanjing China Institute of Computing Technology Chinese Academy and Sciences Beijing China

ISBN: (纸本)0769525210

An orthogonal Chebyshev kernel function for support vector machine (SVM) is proposed based on extensive research about the properties of kernel functions. Chebyshev polynomials are firstly constructed through Chebyshev formulae. Then based on these polynomials Chebyshev kernels are created satisfying Mercer condition. As Chebyshev polynomial has the best uniform proximity and its orthogonality promises the minimum data redundancy in feature space, it is possible to represent the data with less support vectors. Experimental result shows that compared with other tradition support vector machines, Chebyshev kernel support vector machine performs much better and has less support vectors. Chebyshev kernel also has the ability of generalization. It is proved to be an excellent, widely suited and practical kernel both theoretically and experimentally

关键词： Support vector machines Chebyshev approximation Kernel Polynomials Support vector machine classification pattern recognition Equations Machine learning algorithms Handwriting recognition Image recognition

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Emotion and Gesture recognition with soft computing Tool for Drivers Assistance System in Human Centered Transportation

Emotion and Gesture Recognition with Soft Computing Tool for...

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IEEE international conference on Systems, Man, and Cybernetics

作者： Urvashi Agrawal Shubhangi Giripunje Preeti Bajaj PG Dept. of Electronics G.H. Raisoni College of Engineering Nagpur India Ph.D Scholar Dept. of Electronics G.H. Raisoni College of Engineering Nagpur India Professor Dept. of Electronics G.H. Raisoni College of Engineering Nagpur India

ISBN: (纸本)9781479906505

Expression recognition or Emotional state recognition using holistic and feature information is the vital step in Driver Assistance System. Many researchers have work on Facial Gesture or Emotion recognition independently. The purpose of the present paper is to deal with Simultaneous Facial Gesture tracking and Emotion recognition with soft computing tool like Fuzzy rule based system (FBS). In Human Centered Transportation large number of road accidents took place due to drowsiness or bad mood of the driver. The system proposed in this paper take into account both the Facial Gesture tracking and Emotion recognition so that if there is any sign of less attentiveness of the driver or driver's fatigue the car will be switch to automatic mode. A novel fuzzy system is created, whose rules is being defined through analysis of Facial Gesture variations. The idea behind this paper is to detect Facial Gesture by detecting the motion of eyes & lips along with classification of different facial expressions into one of the four basic human emotions, viz. happy, anger, sad, and surprise with fuzzy rule based system for better system performance. The given system proposes 91.66% accuracy for Facial Gesture detection & 90% accuracy for Emotion recognition while using Simultaneous Facial Gesture detection and Emotion recognition it provides 94.58% accuracy.

关键词： HCTS Driver Assistance System (DAS) Facial Gesture Emotion recognition Fuzzy Rule Based System (FBS) emotion recognition Gestures Gesture recognition Drivers Emotions Fuzzy rules Road accidents Face Face transport Driver Assistance Systems fuzzy rule-based system Human soft computing driver circuits

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Visual Informatics: Sustaining Research and Innovations 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Halimah Badioze Zaman Peter Robinson Maria Petrou Patrick Olivier Timothy K. Shih Sergio Velastin Ingela Nyström

ISBN: (数字)9783642252006

ISBN: (纸本)9783642251993

The two-volume set LNCS 7066 and LNCS 7067 constitutes the proceedings of the Second international Visual Informatics conference, IVIC 2011, held in Selangor, Malaysia, during November 9-11, 2011. The 71 revised papers presented were carefully reviewed and selected for inclusion in these proceedings. They are organized in topical sections named computer vision and simulation; virtual image processing and engineering; visual computing; and visualisation and social computing. In addition the first volume contains two keynote speeches in full paper length, and one keynote abstract.

关键词： Image Processing and Computer Vision pattern recognition Computer Graphics Artificial Intelligence Algorithm Analysis and Problem Complexity User Interfaces and Human Computer Interaction

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Advanced computing 1

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丛书名： Communications in Computer and Information Science

1000年

作者： Deepak Garg Suneet Kumar Gupta V. A. Narayana Vijaya Kumar Koppula P. N. Suganthan Jaume Anguera

ISBN: (数字)9783031356414

ISBN: (纸本)9783031356407

This two-volume set constitutes reviewed and selected papers from the 12th international Advanced computing conference, IACC 2022, held in Hyderabad, India, in December 2022.;The 72 full papers and 6 short papers presented in the volume were thorougly reviewed and selected from 415 submissions. The papers are organized in the following topical sections: AI in industrial applications; application of AI for disease classification and trend analysis; design of agricultural applications using AI; disease classification using CNN; innovations in AI; system security and communication using AI; use of AI in human psychology; use of AI in music and video industries.

关键词： Artificial Intelligence Computer Systems Organization and Communication Networks Computer Applications Computers and Education Computer Imaging, Vision, pattern recognition and Graphics

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The Relationship Between Kernel and Classifier Fusion in Kernel-Based Multi-Modal pattern recognition: An Experimental Study

The Relationship Between Kernel and Classifier Fusion in Ker...

引用

international conference on Machine Learning and Cybernetics (ICMLC)

作者： David Windridge Vadim Mottl Alexander Tatarchuk Andrey Eliseyev Centre for Vision Speech and Signal Processing University of Surrey Guildford UK Computing Center Russian Academy of Science Moscow Russia Moscow Institute of Physics and Technology Moscow Russia

Two distinct principles of multi-modal kernel-based pattern recognition, kernel and classifier fusion, are demonstrated to share common underlying characteristics via the use of a novel kernel-based technique for combining modalities under fully general conditions, namely, the neutral-point method. This method presents a conservative kernel-based strategy for dealing with missing and disjoint training data in independent measurement modalities that can be theoretically shown to default to the sum rule classification scheme. Results of comparative experiments indicate that the neutral-point technique loses relatively little classification information with respect to coincident training data, and is in fact preferable for independent kernels produced by different physical modalities due to its better error-cancellation properties.

关键词： Kernel pattern recognition Training data Sensor fusion Machine learning Cybernetics Speech processing Biomedical signal processing Computer vision Physics computing

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A Novel Melanoma Diagnosing System Using Multi-directional pattern Extraction-Based Distributed Deep Learning Model 6th

A Novel Melanoma Diagnosing System Using Multi-directional P...

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6th international conference on Recent Innovations in computing, ICRIC 2023

作者： Pavithra, R. Samraj, Jasmine Chennai India

ISBN: (纸本)9789819728381

Skin cancer is considered among the most threatening types of cancer. The main cause of skin cancer is unrepaired DNA breaks in the skin cells, which lead to inherited defects or irregularities on the skin. It is essential to detect skin cancer early on since it is more curable then and tends to progress gradually to other body regions also. The high fatality rate, increasing prevalence of cases, and high cost of healthcare expenses associated with skin cancer make early detection of behaviors essential. Because of how serious these issues may get, researchers have developed a number of preventive detection methods for skin cancer. This paper suggests a unique deep neural network classifier for skin cancer recognition and classification that is based on pattern extraction. By employing Multi-directional Texture pattern extraction(MDTP) with geometrical details, features that are predictive of cancerous regions will be extracted from the images. These criteria would be picked using Batched Quantum Intensity Spot optimization to improve the segmentation process precision. The model would then be trained using Distributed Deep Learning (DDL), enabling extremely accurate detection of malignant areas in skin images, in order to speed up and increase the segmentation process accuracy. The results of the proposed MDTP-DDL method is validated and assessed by using the public datasets and several performance measures. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Deep neural networks

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Using B-spline curves for hand recognition

Using B-spline curves for hand recognition

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international conference on pattern recognition

作者： YingLiang Ma F. Pollick W.T. Hewitt University of Glasgow Glasgow Glasgow GB Psychology Department University of Glasgow UK

ISBN: (纸本)0769521282

The B-spline curve and surface provide an accurate tool to record object shape. We present a biometric identification system through hand geometry measurements by using B-spline curves. We use 4 B-spline curves to fit with fingers (except thumb) from a single hand image for a single person. Then we store these 4 curves as well as other geometry measurements of the hand as the "signature" of that person into the database. By computing the differences between the curves from database hand images and the curves from the query hand image using the point projection method, we are able to verify/identify the person by locating the closest database hand image to the query hand image.

关键词： Spline Fingers Biometrics Geometry Image databases Spatial databases Fingerprint recognition pattern recognition Shape Iris

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Mutual information based on Renyi's entropy feature selection

Mutual information based on Renyi's entropy feature selectio...

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IEEE international conference on Intelligent computing and Intelligent Systems (ICIS)

作者： Can-Tao Liu Bao-Gang Hu National Laboratory of Pattern Recognition /Sino-French Laboratory in Computer Science Automation and Applied Mathematics Institute of Automation Chinese Academy of Sciences Beijing 100190 China Graduate University of Chinese Academy of Sciences Beijing 100049 China

Feature selection problem has become the focus of much pattern classification research and mutual information is more and more important in the feature selection algorithms. We proposed normalized mutual information based on Renyi's quadratic entropy feature selection, which reduces the computational complexity, relying on the efficient estimation of the mutual information. Then we combine NMIFS with wrappers into a two-stage feature selection algorithm. This helps us find more charactering feature subset. We perform some experiments to compare the efficiency and classification accuracy to other MI-based feature selection algorithm. Results show that our method leads to promising improvement on computation complexity.

关键词： Mutual information Entropy Computational complexity Filters Laboratories pattern recognition Automation Machine learning algorithms Degradation Computer science

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Smart mirror for smart life 6

Smart mirror for smart life

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6th ICT international Student Project conference, ICT-ISPC 2017

作者： Mu’izzudeen Yusri, Muhammad Kasim, Shahreen Hassan, Rohayanti Abdullah, Zubaile Ruslai, Husni Jahidin, Kamaruzzaman Arshad, Mohammad Syafwan Soft Computing and Data Mining Centre Fakulti Sains Komputer dan Teknologi Maklumat Universiti Tun Hussein Onn Malaysia Johor Malaysia Faculty of Computing Universiti Teknologi Malaysia Johor Malaysia GATES IT Solution SDN Bhd Lot 4 Kompleks Usahawan Teknologi MARA Industrial Centre Technovation Park UTM Jalan Pontian Lama Skudai Johor Darul Ta’zim81300 Malaysia Powernode Solution SDN Bhd 33B Jalan Kota Raja F27/F Hicom Town Centre Seksyen 27 Shah Alam Shah Alam Selangor40400 Malaysia

ISBN: (纸本)9781538629963

Internet of Things (IoT) is a concept where an object having the ability to transfer data over a network without the need for human interaction to human or human to computer. IoT is known for its advantage that can help simplify people's everyday routine. Hence, the researcher comes with a proposed system called Smart Mirror. It is a concept of smart home-based Internet of Things (IoT). This system allows users to access information and also control the lights in the house. Relevant information can be traced such as time and date, weather, warning, traffic, and location map. The system applies Sonus technology as a medium of interaction between people and systems. So, users need to provide instructions to the system orally to acquire the system’s response. The methodological approach used in this project is The Evolutionary Prototyping which gathers all requirements and designs the system in a quick method. A prototype is built to evaluate and deliver feedback. Improvements will be made to enhance the prototype, catering to user’s satisfaction. Sonus is a speech to text library that can quickly and easily add a VUI (Voice User Interface) to any hardware or software project. Similar to Alexa, Google Now, and Series, Sonus can always provide listening function offline for a customizable hotword. Once a hotword is detected, it will be streamed to user’s speech recognition cloud service, then the results shall be received. With Smart Mirror system, users can manage their daily activities at ease as well as solving many problems in managing some house chores. © 2017 IEEE.

关键词： Internet of things

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