Search Results - (( feature deviation selection algorithm ) OR ( java application based algorithm ))

Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification by Petwan, Montha

“…The Friedman test result is presented for the performance rank of six benchmark feature selection algorithms and FESSIC algorithm. …”
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Optimal input features selection of wavelet-based EEG signals using GA by Mohd. Daud, Salwani, Yunus, Jasmy

“…A combination of genetic algorithm (GA) and artificial neural network (ANN) are used to select the relevant features. …”
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Feature selection in intrusion detection, state of the art: A review by Rais, H.M., Mehmood, T.

“…In this paper implementation of different feature selection techniques have been reviewed. Novel feature selection techniques have been developed due to its importance in network intrusion domain. …”
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RSA Encryption & Decryption using JAVA by Ramli, Marliyana

“…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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Enhancing high-dimensional streaming data analysis: optimizing Online Feature Selection for handling drift using optimization technique and ensemble learning by Kamaru-Zaman, Ezzatul Akmal

“…In the era of data-driven decision-making, managing dynamic data streams characterized by evolving data distributions and high dimensionality presents a formidable challenge for online feature selection. This research addresses the challenge by devel-oping innovative solutions in optimizing Online Feature Selection (OFS) to manage feature irrelevancy and redundancy, tackling the issues of Feature Drift, and rigor-ously validating the proposed algorithms in high-dimensional dynamic data streams. …”
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Analysis Of Feature Reduction Algorithms To Estimate Human Stress Conditions by Arasu, Darshan Babu

“…Therefore, this study aimed to present analyse of the performance of feature classify when combining with feature selection algorithm to estimate human stress based on the facial feature of thermal imaging. …”
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Statistical band selection for descriptors of MBSE and MFCC-based features for accent classification of Malaysian English / Yusnita M. A. ...[et al.] by M. A., Yusnita, M. P., Paulraj, Yaacob, Sazali, A. B., Shahriman, Mokhtar, Nor Fadzilah

“…This paper proposes an efficient way of analyzing the ethnical accent using statistical knowledge of log-energies of fourier transformed derived mel-filter banks. A simple algorithm to select bands so called statistical band selection (SBS) method using smallest variances within class scores was developed to optimize the presentation of speech features. …”
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Development of a syncope classification algorithm from physiological signals acquired in tilt-table test by Gan, Ming Hong

“…There are 8 set of feature selection model has built and a total of 24 set of classifiers with 3 different type of classification techniques were developed. …”
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Automated plant recognition system based on multi-objective parallel genetic algorithm and neural network by Sefidgar, Seyed Mohammad Hossein

“…Texture features involved the middle energy and the middle entropy and shape features involved statistical characterizations including variance, median, standard deviation and mean. …”
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Improved measurement of blood pressure by extraction of characteristic features from the cuff oscillometric waveform by Lim, P.K., Ng, S.C., Jassim, W.A., Redmond, S.J., Zilany, M., Avolio, A., Lim, E., Tan, M.P., Lovell, N.H.

“…Using the sequential forward floating selection (SFFS) approach, we were able to achieve a significant reduction in the mean and standard deviation of differences between the estimated SBP values and the reference scoring (MLR: mean +/- SD = -0.3 +/- 5.8 mmHg; SVR and -0.6 +/- 5.4 mmHg) with only two features, i.e., Ratio(2) and Area(3), as compared to the conventional maximum amplitude algorithm (MAA) method (mean +/- SD = -1.6 +/- 8.6 mmHg). …”
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Pairwise clusters optimization and cluster most significant feature methods for anomaly-based network intrusion detection system (POC2MSF) / Gervais Hatungimana by Hatungimana, Gervais

“…The unrecognizable IDS; IDS which is neither HIDS nor NIDS is the consequence of using statistical methods for features selection. The speed, memory and accuracy of IDS are affected by inappropriate features reduction method or ignorance of irrelevant features. …”
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Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

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Application of genetic algorithm and JFugue in an evolutionary music generator by Tang, Jia Rou

“…This project explores the application of Genetic Algorithms (GA) with JFugue, which is a Java-based music programming library to develop an Evolutionary Music Generator. …”
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Java based expert system for selection of natural fibre composite materials by Ahmed Ali, Basheer A., Salit, Mohd Sapuan, Zainudin, Edi Syams, Othman, Mohamed

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Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

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Real-Time Video Processing Using Native Programming on Android Platform by Saipullah, Khairul Muzzammil

“…However for the Android platform that based on the JAVA language, most of the software algorithm is running on JAVA that consumes more time to be compiled. …”
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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices by Tran, Duc Ngoc, Hussin, Fawnizu Azmadi, Yusoff, Mohd Zuki

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Real-time algorithmic music composition application. by Yap, Alisa Yi Hui

“…This project is about the study of evolutionary music, and focuses on the development of an algorithmic music composer using the Java programming language. …”
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The classification of EEG signal processing using different machine learning techniques for BCI application by Rashid, Mamunur, Norizam, Sulaiman, Mahfuzah, Mustafa, Sabira, Khatun, Bari, Bifta Sama

“…Finally, the translation algorithm will be con-structed using selected and classified EEG features to control the BCI devices.…”
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Automated characterization of coronary artery disease, myocardial infarction, and congestive heart failure using contourlet and shearlet transforms of electrocardiogram signal by Acharya, U.R., Fujita, H., Sudarshan, V.K., Oh, S.L., Adam, M., Tan, J.H., Koo, J.H., Jain, A., Lim, C.M., Chua, K.C.

“…Only significant features are selected using improved binary particle swarm optimization (IBPSO) feature selection method. …”
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