Search Results - (( features extraction methods algorithm ) OR ( variable extraction method algorithm ))*

Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms by Rachmad, Iqbal, Tri Basuki, Kurniawan, Misinem, ., Edi Surya, Negara, Tata, Sutabri

“…The feature extraction methods evaluated were Grayscale Pixel Values, Mean Pixel Value of Channels, and Extracting Edge Features. …”
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

“…Feature extraction and selection reduces the number of features. …”
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HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC by Jamil, Nur Farahim

“…This project proposes a pattern recognition algorithm consisting of statistical methods to extract seven textural features from the HEp-2 cell images followed by classification of staining patterns by using fuzzy logic. …”
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The impact of the combat method on radiomics feature compensation and analysis of scanners from different manufacturers by Zhang, Xiaolei, Iqbal bin Saripan, M., Wu, Yanjun, Wang, Zhongxiao, Wen, Dong, Cao, Zhendong, Wang, Bingzhen, Xu, Shiqi, Liu, Yanli, Marhaban, Mohammad Hamiruce, Dong, Xianling

“…Conclusions: The Combat algorithm has reduced variability in radiomic features from different scanners. …”
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Chain coding and pre processing stages of handwritten character image file by Suliman, Azizah, Sulaiman, Md. Nasir, Othman, Mohamed, O. K. Rahmat, Rahmita Wirza

“…In this paper detailed descriptions of the algorithms used in the pre-processing and feature extraction phases of an offline handwritten character are discussed. …”
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HEp-2 cell images classification based on statistical texture analysis and fuzzy logic by Jamil, N.F.B., Faye, I., May, Z.

“…This paper proposes a pattern recognition algorithm consisting of statistical methods to extract seven textural features from the HEp-2 cell images followed by classification of staining patterns by using fuzzy logic. …”
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Short-Term Electricity Price Forecasting via Hybrid Backtracking Search Algorithm and ANFIS Approach by Pourdaryaei, Alireza, Mokhlis, Hazlie, Illias, Hazlee Azil, Kaboli, S. Hr. Aghay, Ahmad, Shameem

“…A multi-objective feature selection approach comprises of multi-objective binary-valued backtracking search algorithm (MOBBSA) as an efficient evolutionary search algorithm and ANFIS method is developed in this paper to extract the most influential subsets of input variables with maximum relevancy and minimum redundancy. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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A novel theoretical and practical methodology for extracting the parameters of the single and double diode Photovoltaic models by Mohammed Ridha, Hussein, Hizam, Hashim, Mirjalili, Seyedali, Othman, Mohammad Lutfi, Ya’acob, Mohammad Effendy, Abualigah, Laith

“…However, there is no method to date that can guarantee the extracted parameter of the PV model is the most accurate one. …”
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A new descriptor for smile classification based on cascade classifier in unconstrained scenarios by Hassen, Oday Ali, Abu, Nur Azman, Zainal Abidin, Zaheera, Saad, Mohamed Darwish

“…In this paper, an adaptive model for smile classification is suggested that integrates a row-transform-based feature extraction algorithm and a cascade classifier to increase the precision of facial recognition. …”
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Classification Of Cervical Cancer Stage From Pap Smear Tests by Sendal, Ken Irok

“…During image preprocessing, the image will be converted to greyscale before improving their contrast level for better analysis. Feature extraction is then used to select the appropriate features that contribute most to the predicted variable from the image. …”
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Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei by Alireza , Pourdaryaei

“…In the developed method of multi-objective feature determination, MOBBSA is used to search within different combinations of input variables and to select the non-dominated feature subsets. …”
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Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition by Ali Adlan, Hanan Hassan

“…The RNN was used to detect patterns present in satellite image. A novel feature extraction algorithm was developed to extract the feature vectors. …”
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Computer-aided diagnosis of diabetic subjects by heart rate variability signals using discrete wavelet transform method by Acharya, U.R., Sudarshan, V.K., Ghista, D.N., Lim, W.J.E., Molinari, F., Sankaranarayanan, M.

“…These features are ranked by using various ranking methods, namely, Bhattacharyya space algorithm, t-test, Wilcoxon test, Receiver Operating Curve (ROC) and entropy. …”
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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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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

“…However, existing RUL prediction approaches have difficulties with variability and nonlinearity that occur during battery degradation, data extraction, feature extraction, hyperparameters optimization, and prediction model uncertainty. …”

Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients by Moghbel, Mehrdad

“…This is followed by the clustering of the liver tissues using particle swarm optimized spatial FCM algorithm. Then, these tissues are classified into tumors and blood vessels by an AdaBoost classification method based on tissue features extracted utilizing first, second and higher order image features selected by a minimal-redundancy maximalrelevance feature selection approach. …”
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Feature detector-level fusion methods in food recognition by Razali @ Ghazali, Mohd Norhisham, Manshor, Noridayu

“…Therefore, this paper investigates the methods to fuse multiple features extracted from food images. …”
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Classification and prediction analysis for weld bead surface quality using feature extraction and mahalanobis-taguchi system by Nolia, Harudin, Muhammad Ikmal Hafiz, Mohd Yusof, Zulkifli, Marlah@Marlan, Faizir, Ramlie, Wan Zuki Azman, Wan Muhamad, Mohd Yazid, Abu, Zamzuraida, Baharum

“…The results reveal that while the K-means clustering method outperforms the Variable Bin Width method across several performance metrics, including an accuracy of 86.36% and a high specificity of 94.5%, the method’s recall rate of 50.49% indicates room for improvement in identifying true positives. …”
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A genetic algorithm based fuzzy inference system for pattern classification and rule extraction by Wong S.Y., Yap K.S., Li X.

“…This paper presents a genetic-algorithm-based fuzzy inference system for extracting highly comprehensible fuzzy rules to be implemented in human practices without detailed computation (hereafter denoted as GA-FIS). …”