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Inverse problem in image processing: Image restoration
Published 2023“…In general, the proposed MB-ES on DIP outperforms classical methods and shows comparable performance with recent deep-learning-based models. It is worth noting that DIP does not require heavy training on massive datasets to achieve the performance that DL models possess. …”
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Final Year Project / Dissertation / Thesis -
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A practical and interactive web-based software for online Qur'anic Arabic learning
Published 2016“…The intent of this paper is to summarize and analyze the data and experience earned from a practical implementation of online language learning approach specifically targeted to Qur’anic Arabic learning. …”
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Proceeding Paper -
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A practical and interactive web-based software for online Qur’anic Arabic learning
Published 2017“…The intent of this paper is to summarize and analyze the data and experience earned from a practical implementation of online language learning approach specifically targeted to Qur’anic Arabic learning. …”
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Proceeding Paper -
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Evolving fuzzy grammar for crime texts categorization
Published 2015“…This is one of the criteria practiced in automated text categorization. Machine learning (ML) based methods are the popular solution for this problem. …”
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Simulation of Orthogonal Frequency Division Multiplexing (OFDM) signaling
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Learning Object -
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Computational Thinking : Experiences of Rural Pupils in Sarawak Primary School
Published 2021“…Although the quantitative data does not show promising results, the qualitative data can be used to support the learning experiences and knowledge acquired from the learning activities proposed. …”
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Thesis -
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Machine learning models for predicting the compressive strength of concrete with shredded pet bottles and m sand as fine aggregate
Published 2025“…Machine learning is a critical subset of AI that deliberates the development of self-trained algorithms that use previous databases and analysis for result predictions. …”
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Predicting Diseases Using Multi-BackPropagation
Published 2002“…Multi-network approach does not require any changes in neural network learning algorithm. …”
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Thesis -
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Super resolution imaging using modified lanr based on separable filtering
Published 2019“…Super resolution is then achieved using the regularized patch representation (projection matrix) learned to predict the high resolution image features. …”
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Thesis -
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A robust prioritization framework of data quality dimensions to improve ML-driven healthcare systems using AHP and sensitivity analysis
Published 2025“…In contrast to performance evaluation studies involving machine learning algorithms or classifiers, this research does not encompass the training or comparison of predictive models. …”
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To develop an efficient variable speed compressor motor system
Published 2007“…To achieve a robust controller from variation of motor parameters, a real-time or on-line learning algorithm based on a second order optimization Levenberg-Marquardt is employed. …”
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An efficient anomaly intrusion detection method with evolutionary neural network
Published 2020“…Among these techniques, Artificial Neural Network-Multilayer Perceptron (ANN-MLP) is one of the significant used techniques that has been successful in solving many complex practical problems. However, ANN-MLP without activation function would simply be a linear regression model which has limitation and does not perform well most of the times. …”
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Thesis -
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Calibrating hand gesture recognition for stroke Rehabilitation Internet-of-Things (RIOT) using MediaPipe in smart healthcare systems
Published 2024“…This work aims to address these issues by calibrating hand gesture recognition systems using the Rehabilitation Internet-of-Things (RIOT) framework and examining the effectiveness of machine learning algorithms in conjunction with the MediaPipe framework for gesture recognition calibration. …”
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Correcting blue-shift in single-image dehazing via haze-compensated Von Kries adaptation
Published 2025“…HCCVK integrates a novel red-channel compensation mechanism with Von Kries chromatic adaptation to mitigate wavelength-dependent haze suppression and stabilize chromatic consistency under varying illumination. Unlike learning-based color correction approaches, HCCVK does not require training data, is computationally efficient, and maintains algorithmic interpretability, making it suitable for practical deployment. …”
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A systematic literature review on the application of artificial intelligence in enhancing care for kidney diseases patients
Published 2024“…Fourteen studies published from 2018 to 2024 were reviewed in the systematic review to learn how AI technology was incorporated to improve care for CKD patients. …”
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