Search Results - (( process classification model algorithm ) OR ( processes equalization based algorithm ))

Development of lung cancer prediction system using meta-heuristic optimized deep learning model by Mohamed Shakeel, Pethuraj

“…The algorithm detects the affected region depending on pixel similarity computation process. …”
Get full text
Get full text
Get full text

Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A

“…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40.…”
Get full text
Get full text
Get full text

Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A.

“…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40…”
Get full text
Get full text
Get full text

Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Ahmed Dheyab, Saad, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A

“…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40.…”
Get full text
Get full text
Get full text

Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama

“…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40.…”
Get full text
Get full text
Get full text

Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama

“…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40.…”
Get full text
Get full text
Get full text

Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah by Abu Samah, Abdul Hafiz

“…For the image enhancement process, this thesis has proposed high-pass filter combined with histogram equalization and de-haze algorithm respectively to improve the visual quality of fundus images. …”
Get full text
Get full text

Enhanced emotion recognition in videos: a convolutional neural network strategy for human facial expression detection and classification by Ashraf, Arselan, Gunawan, Teddy Surya, Arifin, Fatchul, Kartiwi, Mira, Sophian, Ali, Habaebi, Mohamed Hadi

“…The Viola-Jones algorithm is then used for face detection on the processed grayscale images. …”
Get full text
Get full text
Get full text
Get full text

Neural network based detection of voice disorders using energy spectrum and equal-loudness contours by Murugesa Pandian, Paulraj, Prof. Madya Dr., Sazali, Yaacob, Prof. Dr., Sivanandam, S. N., Muthusamy, Hariharan, Dr.

Get full text

Skin Colour Detection Based On An Adaptive Multi-Thresholding Technique by Mharib, Ahmed M.

“…The model is based on the bivariate normal distribution of the skin chromatic subspace. …”
Get full text
Get full text

Effective Deep Features for Image Splicing Detection by Ahmed I.T., Hammad B.T., Jamil N.

Development of biosignals-based multimodal biometric system by Osamah Sadeq Alhamdani

“…The success of any biometric system is dependent on the pre-processing, features and classification algorithms exploits. …”
Get full text
Get full text
Get full text

Knowledge base processing method based on text classification algorithm by Baisheng Zhong, Mohd Shamrie Sainin, Tan Soo Fun

“…The text classification algorithm's knowledge base processing method utilizes existing data from the knowledge base to guide the construction and training of the classification model. …”
Get full text
Get full text
Get full text

Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

“…In order to solve it, Bat Algorithm method is implement in to optimization method in fuzzy modeling for classification. …”
Get full text
Get full text
Get full text

A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network by Salari, Nader, Shohaimi, Shamarina, Najafi, Farid, Nallappan, Meenakshii, Karishnarajah, Isthrinayagy

“…The performance of the proposed model was compared with thirteen well-known classification models based on seven datasets. …”
Get full text
Get full text
Get full text

Feature Selection with Harmony Search for Classification: A Review by Norfadzlan, Yusup, Azlan, Mohd Zain, Nur Fatin Liyana, Mohd Rosely, Suhaila Mohamad, Yusuf

“…If the datasets contains irrelevant features, it will not only affect the training of the classification process but also the accuracy of the model. …”
Get full text
Get full text
Get full text

Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
Get full text
Get full text
Get full text

Application of Bat Algorithm and Its Modified Form Trained with ANN in Channel Equalization by Pradyumna Kumar Mohapatra, Saroja Kumar Rout, Sukant Kishoro Bisoy, Sandeep Kautish, Muzaffar Hamzah, Muhammed Basheer Jasser, Ali Wagdy Mohamed

“…An alternative approach to training neural network-based equalizers is to use metaheuristic algorithms. …”
Get full text
Get full text
Get full text
Get full text
Get full text

Development of classification model between clean water and polluted water based on capacitance properties using Levenberg Marquardt (LM) algorithm of artificial neural network / M... by Mohamad Salehuddin, Mohamad Firdaus

“…These measurement inputs were then going through the process of classification in ANN to generate the optimized models by using LM algorithm. …”
Get full text
Get full text

Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif by Jantan, Hamidah, Mat Yusof, Norazmah, Abdul Latif, Mohd Hanapi

“…The objective of this study is to suggest the potential classification model for talent forecasting throughout some experiments using SVM learning algorithm. …”
Get full text
Get full text