Search Results - parallel training ((system algorithm) OR (based algorithm))
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1
A parallel genetic algorithm-based TSK-Fuzzy system for dynamic car-following modeling
Published 2009“…This paper presents the application of Parallel Genetic Algorithm (PGA)-based Takagi Sugeno Kang (TSK)-Fuzzy approach for dynamic car-following modeling in the traffic simulation software. …”
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2
Wavelet network based online sequential extreme learning machine for dynamic system modeling
Published 2013“…In this paper an online sequential extreme learning machine (OSELM) algorithm adopted as training procedure for wavelet network based on serial-parallel nonlinear autoregressive exogenous (NARX) model. …”
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3
A Parallel-Model Speech Emotion Recognition Network Based on Feature Clustering
Published 2023“…Although researchers have made progress in speech emotion feature extraction and model identification, they have struggled to create an SER system with satisfactory recognition accuracy. 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“…Although researchers have made progress in speech emotion feature extraction and model identification, they have struggled to create an SER system with satisfactory recognition accuracy. 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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5
Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Here, the memory consumption can be reduced by enabling a feature selection algorithm that excludes nonrelevant features and preserves the relevant ones. the algorithm is developed based on the variable length of the PSO. …”
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6
Speech compression using compressive sensing on a multicore system
Published 2011“…In order to further reduce the bit requirement, vector quantization using codebook of the training signals will be added to the system. The performance of overall algorithms will be evaluated based on the processing time and speech quality. …”
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Proceeding Paper -
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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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Acquisition of context-based word recognition by reinforcement learning using a recurrent neural network
Published 2012“…The developed learning system has a 4-layered RNN and it was trained by BPTT method based on teaching signal that was generated by Q-Learning algorithm. …”
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9
Acquisition of context-based word recognition by reinforcement learning using a recurrent neural network
Published 2012“…The developed learning system has a 4-layered RNN and it was trained by BPTT method based on teaching signal that was generated by Q-Learning algorithm. …”
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Undergraduates Project Papers -
10
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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11
Empirical analysis of parallel-NARX recurrent network for long-term chaotic financial forecasting
Published 2014“…The main aim of forecasters is to develop an approach that focuses on increasing profit by being able to forecast future stock prices based on current stock data. This paper presents an empirical long term chaotic financial forecasting approach using Parallel non-linear auto-regressive with exogenous input (P-NARX) network trained with Bayesian regulation algorithm. …”
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12
Online teleoperation of writing manipulator through graphics processing unit based accelerated stereo vision
Published 2021“…Therefore, contactless motion trackers such as stereo vision, structured light and time of flight systems were invented to allow natural control with minimum training. …”
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Parallel batch self-organizing map on graphics processing unit using CUDA
Published 2018“…Although the structure of its training algorithm has a high potential for parallelization, focus of the previous efforts has been on the original Step-wise SOM. …”
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Parallel batch self-organizing map on graphics processing unit using CUDA
Published 2018“…Although the structure of its training algorithm has a high potential for parallelization, focus of the previous efforts has been on the original Step-wise SOM. …”
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16
The feature parallelism model of visual recognition
Published 2017“…First, its accuracy rate and training time were compared to those of DeepFace, a leading industry algorithm for face recognition. …”
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An Improve k-NN Classifier using Similarity Distance Plot-Data Reduction and Dask for Big Datasets
Published 2025“…The k-Nearest Neighbour (k-NN) algorithm is one of the most widely used Instance-Based Learning methods due to its simplicity and ease of implementation. …”
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18
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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Improving parallel self-organizing map using heterogeneous uniform memory access / Muhammad Firdaus Mustapha
Published 2018“…The research continues to design a parallel SOM architecture based on literature study and implements on two types of architecture; standard HC and HUMA model. …”
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20
FPGA-enabled binarised convolutional neural networks toward real-time embedded object recognition system
Published 2017“…FPGAs consist of a matrix of reconfigurable logic gates allowing parallel computing which befits most image processing algorithms such as the CNN. …”
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