Search Results - ((pattern classification) OR (data classification)) using

Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

“…In pattern recognition system, achieving high accuracy in pattern classification is crucial. …”
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Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier by Siow, Shien Loong

“…There are a lot of feature extraction methods and classification methods for iris classification. Classic local binary pattern (LBP) is one of the most useful feature extraction methods. …”
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Pattern Recognition for Human Diseases Classification in Spectral Analysis by Nur Hasshima Hasbi, Abdullah Bade, Fuei, Pien Chee, Muhammad Izzuddin Rumaling

“…Typically, pattern recognition consists of two components: exploratory data analysis and classification method. …”
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Songket pattern classification using backpropagation neural network / Nik Aidil Syawalni Nik Mazlan by Nik Mazlan, Nik Aidil Syawalni

“…Despite to the several system limitations, the project on classifies Songket pattern using BPNN is consider successful. The outcomes of this investigation show the originality and efficacy of employing BPNNs for Songket pattern classification, resulting in good accuracy rates in the classification of Songket. …”
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Classification Analysis Of The Badminton Five Directional Lunges by Ho, Zhe Wei

“…REP Tree classifier is the best selected classifier for its strength and classification capability. The highest classification accuracy obtained for experimental data-USM and public data-SEA, were 93.75% and 93.01% respectively on REP Tree classifier. …”
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Visual brain activity patterns classification with simultaneous EEG-fMRI: A multimodal approach by Ahmad, R.F., Malik, A.S., Kamel, N., Reza, F., Amin, H.U., Hussain, M.

“…Machine learning classifier is used for the classification purposes. RESULTS: Results showed that superior classification performance has been achieved with simultaneous EEG-fMRI data as compared to the EEG and fMRI data standalone. …”
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Analysis of partial discharge measurement data using a support vector machine by Aziz N.F.A., Hao L., Lewin P.L.

“…To apply SVM learning in partial discharge classification, data input is very important. The input should be able to fully represent different patterns in an effective way. …”

Agarwood classification based on odor profile using intelligent signal processing technique / Muhammad Sharfi Najib by Najib, Muhammad Sharfi

“…From 32 data sensor arrays, several significant data sensor array have been pre-processed using principal component analysis (PCA) as data reduction process. …”
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Agarwood classification based on odor profile using intelligent signal processing technique by M. S., Najib

“…From 32 data sensor arrays, several significant data sensor array have been pre-processed using principal component analysis (PCA) as data reduction process. …”
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Object categories specific brain activity classification with simultaneous EEG-fMRI by Ahmad, Rana Fayyaz, Malik, Aamir Saeed, Kamel , Nidal, Reza, Faruque

“…We have achieved better classification accuracy using simultaneous EEG-fMRI i.e., 81.8% as compared to fMRI data standalone. …”
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Automated Classification System for HEp-2 Cell Patterns by Nor Shaharim, Nur Ashiqin

“…The third stage feature extraction based on shape properties data extraction. The last stage uses classification based on different properties data abstracted. …”
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Classification Of Brainwave Using Data Mining In Producing An Emotional Model by Khairul Anuar, Nurshuhada Mahfuz, Md Jan Nordin, Waidah Ismail, Mohd Zalisham Jali

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A hybrid-based modified adaptive fuzzy inference engine for pattern classification by Sayeed, Md. Shohel, Ramli, Abdul Rahman, Hossen, Md. Jakir, Samsudin, Khairulmizam, Rokhani, Fakhrul Zaman

“…The performance of the proposed MAFIE is compared with other existing applications of pattern classification schemes using Fisher's Iris data set and shown to be very competitive.…”
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A Classification on Brain Wave Patterns for Parkinson's Patients Using WEKA by Mahfuz, N, Ismail, W, Noh, NA, Jali, MZ, Abdullah, D, bin Nordin, MJ

“…In this paper, classification of brain wave using real-world data from Parkinson's patients in producing an emotional model is presented. …”

Classification of distribution transformer using cluster analysis by Mat Nawi, Nor Azita

“…This paper presents a methodology for classification transformer using Euclidean distance and cluster analysis. …”
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A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition by Babiker, Elsadig Ahmed Mohamed

“…That is, to use training speech patterns to generate classification rules that can be used later to classify input words patterns. …”
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Walking speed classification from marker-free video images in two-dimension using optimum data and a deep learning method by Sikandar, Tasriva, Rahman, Sam Matiur, Islam, Dilshad, Ali, Md. Asraf, Al Mamun, Md. Abdullah, Rabbi, Mohammad Fazle, Kamarul Hawari, Ghazali, Altwijri, Omar, Almijalli, Mohammed, Ahamed, Nizam U.

“…However, the development of successful and highly predictive deep learning architecture depends on the optimal use of extracted data because redundant data may overburden the deep learning architecture and hinder the classification performance. …”
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Walking speed classification from marker-free video images in two-dimension using optimum data and a deep learning method by Sikandar, Tasriva, Rahman, Sam Matiur, Islam, Dilshad, Ali, Md Asraf, Mamun, Md Abdullah Al, Rabbi, Mohammad Fazle, Kamarul Hawari, Ghazali, Altwijri, Omar, Almijalli, Mohammed, Ahamed, Nizam Uddin

“…However, the development of successful and highly predictive deep learning architecture depends on the optimal use of extracted data because redundant data may overburden the deep learning architecture and hinder the classification performance. …”
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Object categories specific brain activity classification with simultaneous EEG-fMRI by Ahmad, R.F., Malik, A.S., Kamel, N., Reza, F.

“…We have achieved better classification accuracy using simultaneous EEG-fMRI i.e., 81.8 as compared to fMRI data standalone. …”
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Classification of lubricant oil geometrical odor-profile using cased-based reasoning by Suhaimi, Mohd Daud, M. S., Najib, Nurdiyana, Zahed, Muhammad Faruqi, Zahari, Nur Farina, Hamidon Majid, Suziyanti, Zaib, Mujahid, Mohamad, Addie Irawan, Hashim, Hadi, Manap

“…The purpose of this study is to classify the lubricant oil degradation level based on odor-pattern that extracted from the odor data that collected using electronic nose. …”
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