Search Results - (( pattern classification parallel algorithm ) OR ( using vectorisation using algorithm ))

3D silhouette rendering algorithms using vectorisation technique from Kedah topography map by Che Mat, Ruzinoor, Nordin, Norani

“…The vectorisation software has been used for producing these data. …”
Get full text
Get full text
Get full text

VLSI Design of a neurohardware processor implementing the Kohonen Neural Network algorithm by Rajah, Avinash

Get full text
Get full text
Get full text

EMG motion pattern classification through design and optimization of neural network by Ahsan, Md. Rezwanul, Ibrahimy, Muhammad Ibn, Khalifa, Othman Omran

“…A back-propagation neural network with Levenberg-Marquardt training algorithm has been utilized for the classification of EMG signals. …”
Get full text
Get full text
Get full text

EMG motion pattern classification through design and optimization of Neural Network by Md. Rezwanul, Ahsan, Muhammad Ibn, Ibrahimy, Othman Omran, Khalifa

Get full text

Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms by Loo, C.K., Liew, W.S., Seera, M., Lim, Einly

“…To further augment the ARTMAP's pattern classification ability, multiple ARTMAPs were optimized via genetic algorithm and assembled into a classifier ensemble. …”
Get full text
Get full text
Get full text

Robust tweets classification using arithmetic optimization with deep learning for sustainable urban living by Hamza, Manar Ahmed, Hassan Abdalla Hashim, Aisha, Motwakel, Abdelwahed, Elhameed, Elmouez Samir Abd, Osman, Mohammed, Kumar, Arun, Singla, Chinu, Munjal, Muskaan

“…In this view, this research develops an arithmetic optimization algorithm with deep learning based tweets classification (AOADL-TC) approach for sustainable living. …”
Get full text
Get full text
Get full text
Get full text

A DNA-dynamic permutation-diffusion algorithm for image encryption using scaling chaotification models and advanced DNA operations by Alkawsi, Gamal, Khairullah, Mustafa Kamil, Baharuddin, Mohd Zafri, Thabit, Reema, Alomari, Mohammad Ahmed, A. Saif, Faten

“…To evaluate the proposed algorithm, extensive experiments have been conducted, and results have been compared with the latest encryption algorithms. …”
Get full text
Get full text
Get full text
Get full text

Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
Get full text
Get full text

An Automated System For Classifying Conference Papers by Ngan, Seon Choon Han

“…The Knowledge Discovery in Databases (KDD) process was followed as a formal data mining methodology where 1000 AI conference papers were carefully collected, pre-processed and transformed to numerical representations through TF-IDF vectorisation. A randomised stratified 5- fold cross validation was then applied on several data mining algorithms and evaluated using the F-measure as a metric. …”
Get full text
Get full text

Fpga-Based Accelerator For The Identification Of Finger Vein Pattern Via K-Nearest Centroid Neighbors by Yew , Tze Ee

“…In recent years, finger vein recognition has emerged as a promising biometric technology due to the fact that each person in this world has unique finger vein pattern. Over the past few years, various finger vein recognition algorithms and techniques have been proposed by researchers and scholars. …”
Get full text
Get full text

Electromygraphy (EMG) signal based hand gesture recognition using Artificial Neural Network (ANN) by Ahsan, Md. Rezwanul, Ibrahimy, Muhammad Ibn, Khalifa, Othman Omran

“…ANNs are particularly useful for complex pattern recognition and classification tasks. The capability of learning from examples, the ability to reproduce arbitrary non-linear functions of input, and the highly parallel and regular structure of ANNs make them especially suitable for pattern recognition tasks. …”
Get full text
Get full text
Get full text

Hybrid harmony search-artificial intelligence models in credit scoring by Goh, Rui Ying

“…This is believed to be due to the different approaches of both classifiers in capturing data pattern for classification. In terms of computational time, compared to GS-tuned models and the respective HS hybrids, the proposed hybrid MHS-SVM and MHS-RF have reported time improvement of more than 50%, while the parallel computation have saved up approximately 80% of the computational time. …”
Get full text
Get full text