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1
Parallel execution of distributed SVM using MPI (CoDLib)
Published 2023“…Support Vector Machine (SVM) is an efficient data mining approach for data classification. However, SVM algorithm requires very large memory requirement and computational time to deal with very large dataset. …”
Conference paper -
2
Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui
Published 2016“…Sensitivity Encoding (SENSE) is a widely used technique to reconstruct the artefact free images from the Parallel MRI (pMRI) aliased data. Reconfigurable hardware based architecture for SENSE has a great potential to provide good quality image reconstruction with significantly less computation time. …”
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Thesis -
3
Development of a parallel clustering of bilingual corpora based on reduced terms
Published 2015“…However, not many works conducted that are related to clustering bilingual documents found, especially for Malay text articles. The quality of clustering bilingual text documents is highly influenced by the quality of the bag-of-word presentation of Malay text articles presented to the clustering algorithm. …”
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4
Adaptive resource allocation for reliable performance in heterogeneous distributed systems.
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Book Section -
5
Electromygraphy (EMG) signal based hand gesture recognition using Artificial Neural Network (ANN)
Published 2011“…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. …”
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Proceeding Paper -
6
Recognizing complex human activities using hybrid feature selections based on an accelerometer sensor
Published 2017“…Wearable sensor technology is evolving in parallel with the demand for human activity monitoring applications. …”
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Article -
7
Hybrid harmony search-artificial intelligence models in credit scoring
Published 2019“…Then, the two types of features importance computed from RF algorithm are utilized for the attributes explanation. …”
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