Search Results - (( using vector based algorithm ) OR ( pattern classification using algorithm ))

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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Modified word representation vector based scalar weight for contextual text classification by Abbas Saliimi, Lokman

“…Based on the acquired results, the experiments reveal that the modified word vectors algorithm can effectively alter original LLM-generated word vectors to reflect intended contexts and can outperform baseline scores in contextual text classification tasks. …”
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Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

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Content adaptive fast motion estimation based on spatio-temporal homogeneity analysis and motion classification by Nisar, Humaira, Malik, Aamir Saeed, Choi, Tae-Sun

“…This is the basis of the proposed algorithm. The proposed algorithm involves a multistage approach that includes motion vector prediction and motion classification using the characteristics of video sequences. …”
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Evaluation of fall detection classification approaches by Kerdegari, Hamideh, Samsudin, Khairulmizam, Ramli, Abdul Rahman, Ghotoorlar, Saeid Mokaram

“…This paper presents the comparison of different machine learning classification algorithms using Waikato Environment for Knowledge Analysis (WEKA) platform for classifying falling patterns from ADL patterns. …”
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Swarm negative selection algorithm for electroencephalogram signals classification by Sahel Ba-Karait, Nasser Omer, Shamsuddin, Siti Mariyam, Sudirman, Rubita

“…The SNS classification model use negative selection and PSO algorithms to form a set of memory Artificial Lymphocytes (ALCs) that have the ability to distinguish between normal and epileptic EEG patterns. …”
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Neural network paradigm for classification of defects on PCB by Heriansyah, Rudi, Syed Al-Attas, Syed Abdul Rahman, Zabidi, Muhammad Mun'im Ahmad

“…A new technique is proposed to classify the defects that could occur on the PCB using neural network paradigm. The algorithms to segment the image into basic primitive patterns, enclosing the primitive patterns, patterns assignment, patterns normalization, and classification have been developed based on binary morphological image processing and Learning Vector Quantization (LVQ) neural network. …”
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A new model for iris data set classification based on linear support vector machine parameter's optimization by Faiz Hussain, Zahraa, Ibraheem, Hind Raad, Alsajri, Mohammad, Ali, Ahmed Hussein, Mohd Arfian, Ismail, Shahreen, Kasim, Sutikno, Tole

“…In this study, we proposed a newly mode for classifying iris data set using SVM classifier and genetic algorithm to optimize c and gamma parameters of linear SVM, in addition principle components analysis (PCA) algorithm was use for features reduction.…”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification by Chong, Hou Ming, Yin Yap, Xien, Seng Chia, Kim

“…This study proposes a system that can classify tomato plant health into five categories of healthy, early blight, late blight, bacterial spot, and yellow leaf curl virus based on their leaves using deep learning algorithms as feature extractors. …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

“…There are two methods in dealing with imbalanced classification problem, which are based on data or algorithmic level. …”
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Herbs recognition based on chemical properties using machine learning algorithm by Mohamad Radzi, Nur Fadzilah, Che Soh, Azura, Ishak, Asnor Juraiza, Hassan, Mohd Khair

“…This method has demonstrated promising results in identifying herb species, and the classification method based on machine learning algorithms has proven successful in recognizing and distinguishing herb species…”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification by Hou Ming Chong, Hou Ming Chong, Xien Yin Yap, Xien Yin Yap, Kim Seng Chia, Kim Seng Chia

“…This study proposes a system that can classify tomato plant health into five categories of healthy, early blight, late blight, bacterial spot, and yellow leaf curl virus based on their leaves using deep learning algorithms as feature extractors. …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification by Hou Ming Chong, Hou Ming Chong, Xien Yin Yap, Xien Yin Yap, Kim Seng Chia, Kim Seng Chia

“…This study proposes a system that can classify tomato plant health into five categories of healthy, early blight, late blight, bacterial spot, and yellow leaf curl virus based on their leaves using deep learning algorithms as feature extractors. …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification by Hou Ming Chong, Hou Ming Chong, Xien Yin Yap, Xien Yin Yap, Kim Seng Chia, Kim Seng Chia

“…This study proposes a system that can classify tomato plant health into five categories of healthy, early blight, late blight, bacterial spot, and yellow leaf curl virus based on their leaves using deep learning algorithms as feature extractors. …”
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Optimized feature construction methods for data summarizations of relational data by Sze, Florence Sia Fui

“…A classification task is commonly performed to discover frequent patterns in the data that can be used to classify new unknown data. …”
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Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network by Zafar, R., Kamel, N., Naufal, M., Malik, A.S., Dass, S.C., Ahmad, R.F., Abdullah, J.M., Reza, F.

“…General linear model (GLM) is used to find the unknown parameters of every individual voxel and the classification is done using multi-class support vector machine (SVM). …”
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Intelligent non-destructive classification of josapine pineapple maturity using artificial neural network by Nazriyah, Haji Che Zan @ Che Zain

“…The results show that the classification using artificial neural network (pattern recognition) involving feature vectors arithmetic average and standard deviation for all channels R, G and B give the average correct classification rate of 88.89%.…”
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Classification Of Hand Movements Based On Discrete Wavelet Transform And Enhanced Feature Extraction by Too, Jing Wei, Abdullah, Abdul Rahim, Mohd Saad, Norhashimah

“…The extracted features are then fed into the machine learning algorithm for classification process. Four popular machine learning algorithms include k-nearest neighbor (KNN), linear discriminate analysis (LDA), Naïve Bayes (NB) and support vector machine (SVM) are used in evaluation. …”
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Non-fiducial based ECG biometric authentication using one-class support vector machine by Hejazi, Maryamsadat, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Hashim, Shaiful Jahari, Abdul Aziz, Ahmad Fazli, Singh, Yashwant Prasad

“…The personal identity verification in a random population using kernel-based binary and one-class Support Vector Machines (SVMs) has been considered by other biometric traits, but has been so far left aside for analysis of ECG signals. …”
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Electroencephalogram-based decoding cognitive states using convolutional neural network and likelihood ratio based score fusion by Zafar, R., Dass, S.C., Malik, A.S.

“…In this hybrid algorithm, convolutional neural network is modified for the extraction of features, a t-test is used for the selection of significant features and likelihood ratio-based score fusion is used for the prediction of brain activity. …”
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