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Machine learning: tasks, modern day applications and challenges
Published 2019“…Machine learning algorithms learned from available data. Further, this learning laid the foundation to develop AI for the various systems around us. …”
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Predictive modelling of nanofluids thermophysical properties using machine learning
Published 2021“…This thesis aimed to develop machine learning algorithms to estimate the thermophysical properties of commonly used nanofluids. …”
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Impact learning: A learning method from feature's impact and competition
Published 2023“…We, moreover, manifest the prevalence of impact learning over the conventional machine learning algorithm.…”
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Machine learning for data classification in construction project planning
Published 2023“…The concept of the Machine Learning is the ability of the machine able to learn the situation with algorithms rules and make a predictions or decision. …”
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Final Year Project / Dissertation / Thesis -
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Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…In order to address the above mentioned challenges, this study is devoted towards the development of a clusterer and a clustering ensemble learning method based on incremental genetic algorithms addressing group unlabeled samples. …”
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Impact learning : A learning method from feature’s impact and competition
Published 2023“…We, moreover, manifest the prevalence of impact learning over the conventional machine learning algorithm.…”
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DEEP LEARNING ALGORITHM IMPLEMENTATION FOR SHIP DETECTION IN SPOT SATELLITE IMAGES
Published 2019“…The deep-learning algorithm to be deployed is Faster R-CNN and to be implemented using MATLAB. …”
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Final Year Project -
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Hybrid Harmony Search Algorithm with Grey Wolf Optimizer and Modified Opposition-based Learning
Published 2019“…Many variants have been developed to cope with this problem and improve algorithm performance. …”
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Deep learning based emotion recognition for image and video signals: matlab implementation
Published 2021“…Five emotions are considered for recognition: angry, happy, neutral, sad, and surprise, compared to previous algorithms. Different pre-processing steps have been carried over data samples, followed by the popular and efficient Viola-Jones algorithm for face detection. …”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…The experimental results showed that the accuracy of the algorithm over the NSL-KDD dataset was 99.72%, with a memory reduction of 10%. …”
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Impact learning: A learning method from feature’s impact and competition
Published 2023“…We, moreover, manifest the prevalence of impact learning over the conventional machine learning algorithm.…”
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Phylogenetic tree classification system using machine learning algorithm
Published 2015“…A study is conducted to develop an automated phylogenetic tree image classification system by using machine learning algorithm. …”
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Final Year Project Report / IMRAD -
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A Truly Online Learning Algorithm using Hybrid Fuzzy ARTMAP and Online Extreme Learning Machine for Pattern Classification
Published 2015“…The idea of developing FAM-OELM is motivated by the ELM concept proposed by Huang et al., for being an efficient learning algorithm that provides better generalization performance at a much faster learning speed. …”
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Adaptive model predictive control based on wavelet network and online sequential extreme learning machine for nonlinear systems
Published 2015“…Recently, an online sequential extreme learning machine (OSELM) algorithm has been introduced based on extreme learning machine (ELM) theories for single hidden layer feedforward neural networks (SLFN) and has been applied for different online applications. …”
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Comparison of supervised machine learning algorithms for malware detection / Mohd Faris Mohd Fuzi ... [et al.]
Published 2023“…Malware has also evolved significantly over the past few years. With the advancement of malware analysis, Machine Learning (ML) is increasingly being used to detect malware. …”
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Federated deep learning for automated detection of diabetic retinopathy
Published 2022“…Federated learning allows deep learning algorithms to learn from a diverse set of data stored in multiple databases. …”
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Proceeding Paper -
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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection
Published 2020“…The second improvement includes the development and use of new Local Search Algorithm with SSA to improve its exploitation. …”
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