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检索条件"任意字段=10th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2018"

共 62 条记录，以下是1-10 订阅

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10th international conference on soft computing and pattern recognition, socpar 2018

10th International Conference on Soft Computing and Pattern ...

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10th international conference on soft computing and pattern recognition, socpar 2018

ISBN: (纸本)9783030170646

the proceedings contain 38 papers. the special focus in this conference is on soft computing and pattern recognition. the topics include: Sentiment Analysis on Tweets for Trains Using Machine Learning;a Genetic Algorithm for Superior Solution Set Search Problem;an Intelligent Tool for Detection of Phishing Messages;discrete Wavelet Transform Application in Variable Displacement Pumps Condition Monitoring;characterizing Parkinson’s Disease from Speech Samples Using Deep Structured Learning;combinatorial Optimization Method Considering Distance in Scheduling Problem;an Improved Gas Classification Technique Using New Features and Support Vector Machines;superior Relation Based Firefly Algorithm in Superior Solution Set Search;learning in Twitter Streams with 280 Character Tweets;retweet Predictive Model for Predicting the Popularity of Tweets;Diverse Ranking Approach in MCDM Based on Trapezoidal Intuitionistic Fuzzy Numbers;handcrafted Descriptors-Based Effective Framework for Off-line Text-Independent Writer Identification;server Load Prediction on Wikipedia Traffic: Influence of Granularity and Time Window;evolutionary Genes Algorithm to Path Planning Problems;An Efficient and Secure Forward Error Correcting Scheme for DNA Data Storage;a Blockchain-Based Scheme for Access Control in e-Health Scenarios;Blockchain-Based PKI for Crowdsourced IoT Sensor Information;the Design of a Cloud Forensics Middleware System Base on Memory Analysis;privacy Enhancement of Telecom Processes Interacting with Charging Data Records;warning of Affected Users About an Identity Leak;network Security Evaluation and Training Based on Real World Scenarios of Vulnerabilities Detected in Portuguese Municipalities’ Network Devices;Decision Tree and MCDA Under Fuzziness to Support E-Customer Satisfaction Survey;a Survey of Blockchain Frameworks and Applications.

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9th international conference on soft computing and pattern recognition, socpar 2017

9th International Conference on Soft Computing and Pattern R...

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9th international conference on soft computing and pattern recognition, socpar 2017

ISBN: (纸本)9783319763569

the proceedings contain 18 papers. the special focus in this conference is on soft computing and pattern recognition. the topics include: Using multiple minimum support to auto-adjust the threshold of support in apriori algorithm;prediction of the degree of Parkinson’s condition using recordings of patients’ voices;an overview of a distributional word representation for an arabic named entity recognition system;discrete particle swarm optimization for travelling salesman problems: new combinatorial operators;on maximal frequent itemsets enumeration;particle swarm optimization as a new measure of machine translation efficiency;Experimental investigation of ant supervised by simplified PSO with local search mechanism (SAS-PSO-2Opt);A human identification technique through dorsal hand vein texture analysis based on NSCT decomposition;obstacle detection algorithm by stereoscopic image processing: navigation assistance for the blind and visually impaired;a simultaneous topic and sentiment classification of tweets;local directional multi radius binary pattern: novel descriptor for face recognition application;content-based image retrieval approach using color and texture applied to two databases (Coil-100 and wang);shape classification using B-spline approximation and contour based shape descriptors;an image processing based framework using crowdsourcing for a successful suspect investigation;recognition and classification of arabic fricative consonants;cancer classification using gene expression profiling: Application of the filter approach with the clustering algorithm.

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8th international conference on soft computing and pattern recognition, socpar 2016

8th International Conference on Soft Computing and Pattern R...

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8th international conference on soft computing and pattern recognition, socpar 2016

ISBN: (纸本)9783319606170

the proceedings contain 70 papers. the special focus in this conference is on soft computing and pattern recognition. the topics include: Toward real-time high-frequency stock monitoring system using ***;sensitivity analysis on effect of biomechanical factors for classifying vertebral deformities;soft feature based personal recognition;a new form of fuzzy reasoning tool to ensure both accuracy and readability;a novel edge based image steganography technique;RDE - reconstructed mutation strategy for differential evolution algorithm;predicting mobile application ratings using artificial neural network;dimensionality reduction of sift descriptor using vector decomposition for image classification;a comparative analysis of the different data mining tools by using supervised learning algorithms;a well organized phrase-based document clustering using ASCII values and adjacency list;reconstruction of 3-dimensional scenes using depth from defocus and artificial neural networks trained on fractals;performance comparison between apache hive and oracle SQL for big data analytics;design of wide beam hexagonal shaped circularly polarized patch antenna for WLAN application;an experimental comparison with time-series methods;advanced deep neural networks for pattern recognition;security enabled cluster head selection for wireless sensor network using improved firefly optimization;chaperoning the optimization of symmetric finFET circuits;solving machine part cell formation problem using genetic algorithm based evolutionary computing;DWT based source localization using microphone array;prevention of illegal content sharing in peer to peer systems;towards designing a framework for practical keystroke dynamics based authentication and exudates in detection and classification of diabetic retinopathy.

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Design and Evaluation of Reinforcement Learning Based AI Agent: A Case Study in Gaming 8th

Design and Evaluation of Reinforcement Learning Based AI Age...

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8th international conference on soft computing and pattern recognition (socpar) / 8th international conference on Computational Aspects of Social Networks (CASoN)

作者： Jayashree, P. Ramakrishnan, K. Anna Univ Dept Comp Technol Madras Inst Technol Madras 600044 Tamil Nadu India

ISBN: (纸本)9783319606187;9783319606170

soft computing is extensively used in the field of computer games to create AI agents for computers. A case study of reinforcement learning is presented, by designing an AI agent for chopsticks game, with a probabilistic algorithm devised to make use of past game experience as its only tool to guide itself to victory. It has been experimentally verified that the AI agent's performance increases with learning and nears saturation beyond a point of learning. Constant order space and time complexity is achieved with proper design of knowledge base.

关键词： AI agent Chopsticks Reinforcement learning Probabilistic model soft computing

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soft Feature Based Personal recognition 8th

Soft Feature Based Personal Recognition

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8th international conference on soft computing and pattern recognition (socpar) / 8th international conference on Computational Aspects of Social Networks (CASoN)

作者： Kulkarni, Sujata Raut, Ranjana Bhosle, Udhav RSTM Univ Nagpur Yeshwantrao Chavan Coll Engn Nagpur 441110 Maharashtra India SGM Univ Amaravati Elect Dept Amaravati 441110 India Univ Mumbai Rajiv Gandhi Inst Technol Bombay Maharashtra India

ISBN: (纸本)9783319606187;9783319606170

Biometric based personal recognition has become the integral part for administrate and operational aspects for private and government sector. this paper proposed the soft feature based personal recognition by integration of unique and non-unique or soft features to improve the performance of biometrics recognition system. the proposed biometrics recognition system uses unique features of back surface of finger called finger knuckle (FK) and complementary features known as soft features such as age and gender of each individual. Further author presents combination Walsh wavelet Transform based finger knuckle features and soft features at score level using Bayes formula. the algorithm is tested on own FK database and results demonstrated that performance of primary FK recognition system has improved by integrating soft features of same traits. Error Equal Rate (EER) of integrated biometrics is 6.5% which is less as compared to primary.

关键词： Primary biometrics Unique feature soft feature Walsh wavelet transform Bayes formula

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Applicability of soft computing and Optimization Algorithms in software Testing and Metrics - A Brief Review 8th

Applicability of Soft Computing and Optimization Algorithms ...

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8th international conference on soft computing and pattern recognition (socpar) / 8th international conference on Computational Aspects of Social Networks (CASoN)

作者： Sharma, Deepak Chandra, Pravin Guru Gobind Singh Indraprastha Univ Univ Sch Informat & Commun Technol Delhi 110078 India

ISBN: (纸本)9783319606187;9783319606170

In spite of many years of work by scientists and specialists on various software qualities, testing stays one of the most broadly honed and concentrated on methodologies for evaluating and improving software quality. Our objective, in this paper, is to present how optimization techniques provide solutions to different and difficult issues in different areas of software engineering. Optimization algorithms are mathematical procedures, which intends to best optimal results for the defect, fault, failure to accomplish tractability, strength, and low arrangement cost. In this paper, a comprehensive overview of software testing and metrics based on soft computing and optimization techniques is presented. In this survey, we try to explain some major problems like defect prediction, software fault prediction and their solutions by soft computing and optimization algorithms. the paper presents an overview of the usage of Mathematical optimization Algorithms and soft computing approaches.

关键词： Optimization algorithms soft computing software testing Metrics software fault prediction

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Deep Learning Approach for recognition of Handwritten Kannada Numerals 8th

Deep Learning Approach for Recognition of Handwritten Kannad...

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8th international conference on soft computing and pattern recognition (socpar) / 8th international conference on Computational Aspects of Social Networks (CASoN)

作者： Ganesh, Anirudh Jadhav, Ashwin R. Pragadeesh, K. A. Cibi Vellore Inst Univ Vellore Tamil Nadu India

ISBN: (纸本)9783319606187;9783319606170

We come across a large volume of handwritten texts in our daily lives and handwritten character recognition has long been an important area of research in pattern recognition. the complexity of the task varies among different languages and it so happens largely due to the similarity between characters, distinct shapes and number of characters which are all language-specific properties. there have been numerous works on character recognition of English alphabets and with laudable success, but regional languages have not been dealt with very frequently and with similar accuracies. In this paper, we explored the performance of Convolutional Neural Networks, and Deep Belief Networks in the classification of Handwritten Kannada numerals, and conclusively compared the results obtained. the proposed method has shown satisfactory recognition accuracy in light of difficulties faced with regional languages such as similarity between characters and minute nuances that differentiate them. We can further extend this to all the Kannada characters.

关键词： Deep Belief Networks Convolutional Neural Networks LeNet pattern recognition Restricted boltzmann machine Deep learning

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Hybrid soft computing Methods for Prediction of Oil Prices 6

Hybrid Soft Computing Methods for Prediction of Oil Prices

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6th international conference on soft computing and pattern recognition (socpar)

作者： Gabralla, Lubna A. Abraham, Ajith Sudan Univ Sci & Technol Fac Comp Sci & Informat Technol Khartoum Sudan Machine Intelligence Res Labs Auburn WA USA VSB Tech Univ Ostrava IT4Innovat Ostrava Czech Republic

ISBN: (纸本)9781479959341

this paper aims to provide combination of multiple prediction models using different strategies including ensemble selection, voting, stacking and multi-schemes to design a model capable of predicting oil prices accurately. Daily data from 1999 to 2012 with 14 variables were used, which were further divided into 10 sub-datasets according to various attribute selection methods. Four groups of training and testing were examined. Experimental results conclude that performance of the combination model works better than author's previous work and ensemble selection outperforms other combination methods.

关键词： ensemble selection vote stacking multi-scheme prediction oil prices

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Advanced Deep Neural Networks for pattern recognition: An Experimental Study 8th

Advanced Deep Neural Networks for Pattern Recognition: An Ex...

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8th international conference on soft computing and pattern recognition (socpar) / 8th international conference on Computational Aspects of Social Networks (CASoN)

作者： Padmanabhan, Jayashree Premkumar, J. Melvin Jose Anna Univ Madras Inst Technol Madras 600044 Tamil Nadu India Google Inc Software Engn Intern Mountain View CA 94043 USA

ISBN: (纸本)9783319606187;9783319606170

Difficulty in pattern recognition is perceptible and neural networks approach the problem by way of learning from similar known patterns. Interest in Neural Networks started in the early 1980s when they were deemed to effectively model the human thought process. Speech recognition which first used Artificial Neural Networks (ANNs) to model the states of a Hidden Markov Models (HMMs) later started using Gaussian Mixture Models (GMMs). GMM-HMM systems have been the standard until recently when a new concept of Deep Neural Networks (DNNs) pre-trained using Restricted Boltzmann Machines (RBMs) came into existence. the discriminative capability of the resulting DNN is found to improve the performance of the recognition systems. the experimental work with DNN for recognizing patterns in handwriting and speech corpus has been carried out. In this work we implemented Deep Neural Networks for the above tasks and the pre trained DNN has been used for extracting bottleneck features and hereby improving the performance of the baseline systems with respect to recognition errors.

关键词： Deep Neural Networks Boltzmann machine Speech recognition Artificial Neural Networks Machine learning

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Multivariate Analysis of Text Data from Image Information Acquired by Wearable Device 10

Multivariate Analysis of Text Data from Image Information Ac...

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Joint 10th international conference on soft computing and Intelligent Systems (SCIS) / 19th international Symposium on Advanced Intelligent Systems (ISIS)

作者： Domoto, Eri Shibata, Junko Fukushima, Mizuki Okuhara, Koji Hiroshima Univ Econ Fac Econ Hiroshima Japan Kobe Gakuin Univ Fac Econ Kobe Hyogo Japan Fujitsu Hokuriku Syst Ltd Kanazawa Ishikawa Japan Toyama Prefectural Univ Grad Sch Engn Toyama Japan

ISBN: (纸本)9781538626337

In this study, we obtain life log data from visibility information using smart glass which is a wearable device. In the proposed system, it consists of a text data collection part by cooperation between smart glass and image recognition API and activity recognition part. the activity recognition part incorporates multidimensional scaling analysis method and correspondence analysis for classifying data. As a result of utilizing the development system in real life, it was able to detect similarities and events for behavior from the difference of the object caught on sight.

关键词： Multivariate Analysis Life Log Behavior pattern Text Data Mining

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