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101
Extreme learning machines for feature learning
Published 2017“…Hence this thesis extends ELM for feature learning. This thesis introduces an ELM based feature learning framework with linear hidden layer activation function referred to as linear Extreme Learning Machine Auto-Encoder (ELM-AE) and linear Sparse Extreme Learning Machine Auto-Encoder (SELM-AE); ELM-AE and SELM-AE with sigmoid hidden layer activation function referred to as non-linear ELM-AE and non-linear SELM-AE. …”
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Thesis -
102
Indoor occupancy estimation using environmental parameters
Published 2017“…The FS-ELM is in fact a novel architecture of the ELM, in which a feature layer is added to the standard ELM. …”
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Thesis-Doctor of Philosophy -
103
Weighted online sequential extreme learning machine for class imbalance learning
Published 2013“…In this paper, we propose a weighted online sequential extreme learning machine (WOS-ELM) algorithm for class imbalance learning (CIL). …”
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Journal Article -
104
Short-term load forecasting by wavelet transform and evolutionary extreme learning machine
Published 2015“…Each component of the load series is then separately forecasted by a hybrid model of ELM and MABC (ELM-MABC). The global search technique MABC is developed to find the best parameters of input weights and hidden biases for ELM. …”
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Journal Article -
105
Extreme learning machine based fast object recognition
Published 2014“…Besides, the parameter tuning process for ELM is much easier than SVM as well.…”
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Conference Paper -
106
Sequential learning for extreme learning machine
Published 2008“…A novel sequential learning algorihtm for training Single Hidden Layer Feedforward Neural Network (SLFN), Online Sequential Extreme Learning Machine (OS-ELM) is proposed. OS-ELM is based on the combination of Extreme Learning Machine (ELM) and the recursive least-squares (RLS) algorithm. …”
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Thesis -
107
Extreme learning machine for classification and clustering on multiview data
Published 2021“…The ELM auto-encoder (ELM-AE) is adopted for feature extraction and feature fusion, and an ELM classifier is ultilized for the final classification. …”
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Thesis-Doctor of Philosophy -
108
Enhanced extreme learning machines for image classification
Published 2019“…Among numerous machine learning methods, we choose the Extreme Learning Machine (ELM) for our image classification applications. …”
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Thesis -
109
Development of localization algorithms for a WiFi based indoor positioning system with machine learning techniques
Published 2015“…We model the indoor positioning problem under a non-parametric stochastic framework, and modify the well-known ML tool, extreme learning machine (ELM), to achieve the above goal. Firstly, under the assumption that noises merely lie in input data, we modify ELM by introducing a dead zone, which is called DZ-ELM, and integrate it into our IPS. …”
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Thesis -
110
Extreme learning machine based speaker recognition
Published 2011“…Finally and most importantly, the performance of ELM and SVM will be compared. With the results shown in Chapter 6, we can draw the conclusion that ELM is superior to SVM in terms of tuning simplicity, time efficiency and testing accuracy.…”
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Final Year Project (FYP) -
111
ADC architectures for low power analog machine learning
Published 2016“…First, a 1-bit ADC (current comparator) is designed for application in a novel ELM based conditional branch prediction system designed for pipelined processors. …”
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Final Year Project (FYP) -
112
EEG based mind controlled car
Published 2015“…Furthermore, in order to demo the result, we built a remote control car which controlled by the classification result from ELM classifier.…”
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Final Year Project (FYP) -
113
Emotional states classification from brain signals
Published 2013“…Results from the experimental data have indicated that Kernel ELM is the best option as opposed to other SVM variants. …”
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Final Year Project (FYP) -
114
Low-power processors for implantable epileptic seizure detection system
Published 2013“…Extreme Learning Machine (ELM) has gained some attentions recently, due to the fact that learning speed of ELM is really fast compared to the traditional learning algorithm. …”
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Final Year Project (FYP) -
115
Structured sparse representations for supervised and unsupervised learning
Published 2020“…This thesis also explores the use of unsupervised ELM (US-ELM) on top of the learned graph to learn a flexible and discriminative data embedding that is beneficial for clustering. …”
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Thesis-Doctor of Philosophy -
116
Automatic knee segmentation from multi-contrast MR images
Published 2013“…The choice of the classifier can be some powerful classification models such as SVM and ELM. The advantages of the developed scheme are achieved via effective incorporation of both a useful feature set and the ELM (or SVM) classification with spatial dependencies between neighboring voxels via a DRF framework. …”
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Thesis -
117
A collaborative model in persuasive web design: multiple case study of Lazada and Shopee
Published 2023“…This study examined online persuasion through website design by using the Elaboration Likelihood Model (ELM) and Persuasive System Design (PSD). This study investigates the phenomenon of the success of Lazada and Shopee to provide guidelines for website designers and local sellers to enhance the e-commerce website’s persuasiveness. …”
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Conference or Workshop Item -
118
Geometry guided supervised representation learning for classification
Published 2020“…The extreme learning machine auto-encoder (ELM-AE) is an extension of ELM, which is well-known for its fast training speed and strong generalization ability. …”
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Thesis-Doctor of Philosophy -
119
Mitigation study and approach for safe drone operations in low-altitude environments
Published 2022“…The average accuracy and macro-averaged F1 scores for the OS-Fuzzy- ELM fault diagnosis model are 80.2% and 78.0%.…”
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Final Year Project (FYP) -
120
Investigation of fluorescence lifetime imaging for quantitative cervical cancer screening and diagnosis
Published 2015“…The results suggest that the proposed fluorescence lifetime imaging of H&E stained cervical tissue sections with the quantitative neural network ELM could be used to aid and supplement the traditional histopathological examinations. …”
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Thesis