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Quick extreme learning machine for large-scale classification
The extreme learning machine (ELM) is a method to train single-layer feed-forward neural networks that became popular because it uses a fast...
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A learning-based efficient query model for blockchain in internet of medical things
This paper proposes a learning-based model for the resource-constrained edge nodes in the blockchain-enabled Internet of Medical Things (IoMT)...
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Detection of abnormal brain in MRI via improved AlexNet and ELM optimized by chaotic bat algorithm
Computer-aided diagnosis system is becoming a more and more important tool in clinical treatment, which can provide a verification of the doctors’...
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Kernel risk-sensitive mean p-power loss based hyper-graph regularized robust extreme learning machine and its semi-supervised extension for sample classification
Extreme learning machine (ELM) has fast learning speed and perfect performance, at the same time, ELM provides a unified learning framework with a...
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Data stream classification using a deep transfer learning method based on extreme learning machine and recurrent neural network
Deep learning-based approaches have gained popularity for many applications in recent years and have become the state-of-the-art method in machine...
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Random vector functional link network with subspace-based local connections
A new random vector functional link (RVFL) network with subspace-based local connections (abbreviated as RVFL-SLC network) is proposed in this paper....
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Survey on extreme learning machines for outlier detection
In a two-class classification task, if the number of examples of one class (majority) is much greater than that of another class (minority), then the...
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A novel lithium-ion battery capacity prediction framework based on SVMD-AO-DELM
Accurate and efficient lithium-ion battery capacity prediction plays an important role in improving performance and ensuring safe operation. In this...
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SELM: Siamese extreme learning machine with application to face biometrics
Extreme learning machine (ELM) is a powerful classification method and is very competitive among existing classification methods. It is speedy at...
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Benchmarking Training Methodologies for Dense Neural Networks
Multi-Layer Perceptrons (MLP) trained using Back Propagation (BP) and Extreme Learning Machine (ELM) methodologies on highly non-linear,...
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Channel estimation of non-orthogonal multiple access systems based on L2-norm extreme learning machine
In this paper, we study non-orthogonal multiple access (NOMA) transmission system which is a promising technology in future 5G mobile communications....
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Speech emotion recognition using optimized genetic algorithm-extreme learning machine
Automatic Emotion Speech Recognition (ESR) is considered as an active research field in the Human-Computer Interface (HCI). Typically, the ESR system...
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Ensemble-Based Road Surface Crack Detection: A Comprehensive Approach
The existence of road surface cracks erodes the structural robustness of the infrastructure and casts shadows of risks for countless motorists and...
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ELM-MVD: An Extreme Learning Machine Trained Model for Malware Variants Detection
Malware variants are expanding at a fast pace and detecting them is a critical problem. According to surveys from McAfee, over 50% of the newly...
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The ST-GRNN Cooperative Training Model Based on Complex Network for Air Quality Prediction
In recent years, air pollution forecasting has become an important reference for governments when formulating environmental policies. However,...
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Randomized Convolutional Neural Network Architecture for Eyewitness Tweet Identification During Disaster
During a disaster, Twitter is flooded with disaster-related information. Among huge disaster-related Twitter posts, a fraction of them is posted by...
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Semantic hand gesture integration system using self-co-articulation and movement epenthesis detection
Recognizing hand gestures poses a formidable challenge, particularly when dealing with semantic gestures that require disentanglement prior to...
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Laplacian Generalized Eigenvalues Extreme Learning Machine
Semi-supervised learning is an attractive technique for using unlabeled data in classification. In this work, an efficient semi-supervised extreme...
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Effective forecasting of stock market price by using extreme learning machine optimized by PSO-based group oriented crow search algorithm
Stock index price forecasting is the influential indicator for investors and financial investigators by which decision making capability to achieve...
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Applying an Efficient AI Approach for the Prediction of Bearing Capacity of Shallow Foundations
This study focused on presenting the potential of artificial intelligence (AI) modeling approach to predict the bearing capacity (...