Search Results - parallel computer training algorithm~
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Image classification using two dimensional wavelet coefficients with parallel computing
Published 2020“…In addition, this research does not require any pre-stored database to train the algorithm. This research requires the supervision from the users to train the algorithm by naming the region. …”
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Final Year Project / Dissertation / Thesis -
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Parallel batch self-organizing map on graphics processing unit using CUDA
Published 2018“…The most computationally expensive parts of its training algorithm (such as steps to compute distance between each data vector and neuron, and determining the Best Matching Unit based on minimum distance) are identified and mapped on GPU to be processed in parallel. …”
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Parallel batch self-organizing map on graphics processing unit using CUDA
Published 2018“…The most computationally expensive parts of its training algorithm (such as steps to compute distance between each data vector and neuron, and determining the Best Matching Unit based on minimum distance) are identified and mapped on GPU to be processed in parallel. …”
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Computationally efficient sequential learning algorithms for direct link resource-allocating networks
Published 2005“…Computationally efficient sequential learning algorithms are developed for direct-link resource-allocating networks (DRANs). …”
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Improving parallel self-organizing map using heterogeneous uniform memory access / Muhammad Firdaus Mustapha
Published 2018“…Therefore, the main goal of this research is to reduce computation time of SOM training through implementing on HUMA platform and improve GPU cores utilization. …”
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Thesis -
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Hybrid Machine Translation Using Malay-English Language Parallel Text Extraction From Comparable Text
Published 2024“…We improve the bleu score from 13.40% to 15.41% using 315,194 parallel texts. In the second problem, we propose an algorithm to extract parallel sentences and parallel fragments/subsentences from comparable texts. …”
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Protein secondary structure prediction from amino acid sequences using a neural network classifier based on the Dempster-Shafer theory
Published 2003“…In order to reduce the computational demand when training with large data of proteins, an interface was developed using the data parallel approach to parallelize the training phase of the classifier and other accompanying methods such as data clustering algorithms. …”
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Thesis -
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Improving parallel Self-organizing Map using heterogeneous uniform memory access / Muhammad Firdaus Mustapha
Published 2018“…Therefore, the main goal of this research is to reduce computation time of SOM training through implementing on HUMA platform and improve GPU cores utilization……”
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Book Section -
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A Parallel-Model Speech Emotion Recognition Network Based on Feature Clustering
Published 2023“…To address this issue, we proposed a novel algorithm called F-Emotion to select speech emotion features and established a parallel deep learning model to recognize different types of emotions. …”
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A parallel-model speech emotion recognition network based on feature clustering
Published 2023“…To address this issue, we proposed a novel algorithm called F-Emotion to select speech emotion features and established a parallel deep learning model to recognize different types of emotions. …”
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Face recognition using artificial neural networks in parallel architecture
Published 2023“…There, we consider a parallel training approach for backpropagation algorithm for face recognition. …”
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Measuring GPU-accelerated parallel SVM performance using large datasets for multi-class machine learning problem
Published 2023Conference Paper -
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EMG motion pattern classification through design and optimization of neural network
Published 2012“…Extracted time and time-frequency based feature sets are used to train the neural network. A back-propagation neural network with Levenberg-Marquardt training algorithm has been utilized for the classification of EMG signals. …”
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Proceeding Paper
