Search Results - (( developing dynamic recognition algorithm ) OR ( java data optimization algorithm ))
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1
Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition
Published 2010“…In this paper, a new cue-based model for dialogue act recognition is presented. The model is, essentially, a dynamic Bayesian network induced from manually annotated dialogue corpus via dynamic Bayesian machine learning algorithms. …”
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VOICE RECOGNITION FOR SECURITY PURPOSES
Published 2007“…This report presents the implementation of Voice Recognition System for Security Purposes. The scope of study is to understand the existing algorithms and develop a brand new algorithm which is better in terms of its reliability and accuracy. …”
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Final Year Project -
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A sequential handwriting recognition model based on a dynamically configurable convolution recurrent neural network and hybrid salp swarm algorithm
Published 2024“…This research present a dynamic configurator of the CRNN (DC-CRNN), geared for sequence learning in the context of handwriting recognition, inspired by bio-inspired approaches. …”
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4
Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. …”
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Undergraduates Project Papers -
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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6
Animal voice recognition for identification (ID) detection system
Published 2011“…In this paper, an animal identification (ID) detection system based on animal voice pattern recognition algorithm has been developed. The developed animal voice recognition system uses the zero-cross-rate (ZCR), Mel-Frequency Cepstral Coefficients (MFCC) and Dynamic Time Warping (DTW) joint algorithms as the tools for recognizing the voice of the particular animal. …”
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Object with symmetrical pattern recognition with dynamic size filter
Published 2011“…This paper presents the implementation of object with symmetrical pattern recognition algorithm for 2D vision system of 3D vision-based multi sensor feedback system. …”
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9
Dog voice identification (ID) for detection system
Published 2012“…In this paper, an animal identification (ID) detection system based on animal voice pattern recognition algorithm has been developed. The developed animal voice recognition system uses the zero-cross-rate (ZCR), Mel-Frequency Cepstral Coefficients (MFCC) and Dynamic Time Warping (DTW) joint algorithms as the tools for recognizing the voice of the particular animal. …”
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10
A sequential handwriting recognition model based on a dynamically configurable CRNN
Published 2021“…Because most applications of handwriting recognition in real life contain sequential text in various languages, there is a need to develop a dynamic handwriting recognition system. …”
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Feature fusion using a modified genetic algorithm for face and signature recognition system
Published 2015“…This thesis focuses on the development of feature level fusion of bimodal biometrics system for face and dynamic signature recognition system The modalities of biometric are used due to the ability to avoid spoof attack since it is difficult for impostor to imitate two different characteristics (behaviour and physical) at the same time. …”
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Thesis -
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DYNAMIC SIGN LANGUAGE RECOGNITION AND TRANSLATION THROUGH DEEP LEARNING: A SYSTEMATIC LITERATURE REVIEW
Published 2024“…Notably, there have been considerable development in isolated and continuous SLRT models, particularly through the combinations of deep learning algorithms such as Convolutional Neural Network, Recurrent Neural Network and Transformer models, with suitable datasets. …”
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A random search based effective algorithm for pairwise test data generation
Published 2011“…This paper proposes an effective random search based pairwise test data generation algorithm named R2Way to optimize the number of test cases. …”
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Conference or Workshop Item -
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An improved method in speech signal input representation based on DTW technique for NN speech recognition system
Published 2007“…The paper also proposes the use of pitch feature derived from the recorded speech data as another input feature. The Dynamic Time Warping algorithm (DTW) is the back–bone of the newly developed algorithm called DTW fixing frame algorithm (DTW–FF) which is designed to perform template matching for the input preprocessing. …”
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Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition
Published 2004“…The hybrid approaches developed in this thesis provide novel techniques to recognition static and dynamic representation of patterns. …”
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Automated music chord recognition system using Convolutional Neural Network (CNN) / Abdul Qhadir Jailani Azhari
Published 2025“…The main objectives include analysing existing chord recognition algorithms, creating a prototype for real-time chord identification, and testing its performance with music recordings. …”
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Development and analysis of face recognition system on a mobile robot environment / Jit Shen Quah and Mariam Md Ghazaly
Published 2018“…This is done via integrating a developed face recognition software onto a mobile robot in terms of image captured distance and in extension its accuracy during static and dynamic conditions. …”
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Scalable approach for mining association rules from structured XML data
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EasyA: Easy and effective way to generate pairwise test data
Published 2013“…This paper proposes a matrix based calculation for pairwise test data generation algorithm named EasyA to optimize the number of test cases. …”
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Conference or Workshop Item -
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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