Search Results - (( using optimization method algorithm ) OR ( features extraction function algorithm ))

Estimating Face Emotion using Genetic Algorithm by Karthigayan, M., Mohd Rizon, Muhamed Juhari, Sazali, Yaacob, Nagarayan, R.

Subjects: “…Feature extraction…”
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Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection by Too, Jing Wei, Abdullah, Abdul Rahim

“…The proposed CGWO and OBCGWO are then applied to select the relevant features from the original feature set. Four state-of-the-art algorithms include particle swarm optimization, flower pollination algorithm, butterfly optimization algorithm, and CBGWO are used to examine the effectiveness of proposed methods in feature selection. …”
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A new approach for recognition of human emotions by Karthigayan, M., Mohd Rizon, Muhamed Juhari, Sazali, Yaacob, Nagarajan, R.

Subjects: “…Feature extraction…”
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Development of a personified face emotion recognition technique using fitness function by Muthukaruppan, Karthigayan, Mohd Rizon, Mohamed Juhari, Ramachandran, Nagarajan, Masanori, Sugisaka, Sazali, Yaacob, Mohd Rozailan, Mamat, Hazry, Desa

Subjects: “…Feature extraction…”
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Japanese face emotions classification using lip features by Mohamad Rizon, Mohamed Juhari, Muthukaruppan, Karthigayan, Sazali, Yaacob, Nagarajan, R.

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Fuzzy clustering for genetic algorithm based optimized ellipse data in classifying face emotion by Muthukaruppan, Karthigayan, Mohd Rizon, Mohamed Juhari, Sazali, Yaacob, Ramachandran, Nagarajan, Masanori, Sugisaka, Mohd Rozailan, Mamat

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Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals by Too, Jing Wei

“…The first method is the Binary Tree Growth Algorithm (BTGA), which implements a hyperbolic tangent function to convert the Tree Growth Algorithm into the binary version. …”
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Personalized human emotion classification using genetic algorithm by Mohd Rizon, Hazry, Desa, Karthigayan, M., Nagarajan, Ramachandran, Alajlan, N., Sazali, Yaacob, Prof. Dr., Nor Azmi, Johari, Ina Suryani, Ab Rahim

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Computational Technique for an Efficient Classification of Protein Sequences With Distance-Based Sequence Encoding Algorithm by Iqbal, M.J., Faye, I., Said, A.M.D., Samir, B.B.

“…A statistical metric-based feature selection algorithm is then adopted to identify the reduced set of features to represent the original feature space. …”
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EEG classification using radial basis PSO neural network for brain machine interfaces by Paulraj, Murugesapandian, Hema, Chengalvarayan Radhakrishnamurthy, Ramachandran, Nagarajan, Sazali, Yaacob, Abdul Hamid, Adom

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Discrete wavelet packet transform for electroencephalogram based valence-arousal emotion recognition by Olakunle, Oyenuga Wasiu

“…The result of the first experiment showed that entropy features extracted using DWPT are better than bandpower features. …”
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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis by Norman, Masayu

“…A spatio-statistical optimization technique that combines the Taguchi statistical method and a spatial plateau objective function (POF) was presented to improve the segmentation procedures for building footprint extraction. …”
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Noise eliminated ensemble empirical mode decomposition scalogram analysis for rotating machinery fault diagnosis by Atik, Faysal

“…Artificial intelligence can be applied in fault feature extraction and classification. It is crucial to use an effective feature extraction method to obtain most of the fault information and a robust classifier to classify those features. …”
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A preliminary study on automated freshwater algae recognition and classification system / Hayat Mansoor Abdullah by Mansoor Abdullah, Hayat

“…Then principal component analysis (PCA) was applied to normalize the extracted features.Novel techniques of auto-alignments with shape index procedures was developed here,where auto-alignments function was used to aligned image objects with horizontal coordinates to extracted object features in similar position. …”
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The classification of wink-based eeg signals by means of transfer learning models by Jothi Letchumy, Mahendra Kumar

“…This study aimed to explore the performance of different pre-processing methods, namely Fast Fourier Transform, Short-Time Fourier Transform, Discrete Wavelet Transform, and Continuous Wavelet Transform (CWT) that could allow TL models to extract features from the images generated and classify through selected classical ML algorithms . …”
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Color Image Segmentation Based on Bayesian Theorem for Mobile Robot Navigation by Rahimizadeh, Hamid

“…The estimation of unknown PDF is a common problem and in this study Gaussian kernel function which is most widely used nonparametric density estimation method has been used for PDF calculation. …”
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PREDICTIVE MAXIMUM POWER POINT TRACKING (MPPT) ALGORITHM FOR PERMANENT EXCHANGE MEMBRANE FUEL CELL (PEMFC) by MOHD RIZZWAN, MINGGU

“…This maximum output can be determined by using MPPT method such as P&O, INC, FLC, PSO, MPC and more. …”
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Removal of BCG artefact from concurrent fMRI-EEG recordings based on EMD and PCA by Javed, E., Faye, I., Malik, A.S., Abdullah, J.M.

“…One such problematic artefact is the ballistocardiogram (BCG) artefact. Methods We developed a hybrid algorithm that combines features of empirical mode decomposition (EMD) with principal component analysis (PCA) to reduce the BCG artefact. …”
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Vehicle logo recognition using whitening transformation and deep learning by Soon, Foo Chong, Khaw, Hui Ying, Chuah, Joon Huang, Kanesan, Jeevan

“…Unlike most of the common traditional methods that employ handcrafted visual features, our proposed method is able to automatically learn and extract high-level features for the classification task. …”
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Task-state EEG signal classification for spatial cognitive evaluation based on multiscale high-density convolutional neural network by Wen, Dong, Li, Rou, Tang, Hao, Liu, Yijun, Wan, Xianglong, Dong, Xianling, Saripan, M. Iqbal, Lan, Xifa, Song, Haiqing, Zhou, Yanhong

“…Besides, the multi-dimensional conditional mutual information method was used to extract the frequency band features of the EEG data. …”
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