Extreme Learning Machine (ELM)
A New Health Assessment Prediction Approach: Multi-Scale Ensemble Extreme Learning Machine
... named Extreme Learning Machine (ELM) has been spread wide to fit many prediction applications under different ...biological learning and Artificial Neural Networks (ANN) by introducing a new ...
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Accelerating Extreme Learning Machine on FPGA by Hardware Implementation of Given Rotation - QRD
... However, software-based implementation of Moore-Penrose pseudo-inverse consumes a lot of computational time due to the limitations of sequential-based processing of the general purpose processor which only able to ...
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A Novel Approach for Recognizing Facial Structures Using Extreme Learning Machine Algorithm
... Recently, Extreme Learning Machine has been proposed, which significantly decrease the quantity of time needed to train a Neural ...simple learning algorithm for SLFNs called extreme ...
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Convolutional neural network extreme learning machine for effective classification of hyperspectral images
... In this paper, a convolutional neural network extreme learning machine (CNN-ELM) approach is proposed for hyperspectral image classification. Inspired by the reference (Khan et al. 2017), we get the ...
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Multilayer probability extreme learning machine for device-free localization
... Deep learning approaches have attempted to automatically extract the useful information from the links, but the training of the conventional deep learning approaches are time-consuming, because a large ...
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Children Abnormal GAIT Classification Using Extreme Learning Machine
... Vector Machine (SVM) is widely applied in pattern recognition because of its remarkable learning ...the Extreme Learning Machine (ELM) for gait analysis in this paper ...
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Integrating Data Selection and Extreme Learning Machine for Imbalanced Data
... Extreme Learning Machine (ELM) is one of the artificial neural network method that introduced by Huang, this method has very fast learning ...and extreme learning machine ...
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Kernel Based Extreme Learning Machine in Identifying Dermatological Disorders
... much time in adjusting parameters during training. So, in DL training speed is very slow. In [13] convolutional extreme learning machine with kernels (CKELM) was proposed. The hidden layer of CKELM ...
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Integrating Intrusion Detection Model Using Ensemble of Classifiers and Extreme Learning Machine
... with machine learning technique and analysis for huge data is very much ...the Extreme learning machine would be the best suitable for IDS with the analysis of big data and improving ...
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Recognition of Facial Structures Using Extreme Learning Machine Algorithm
... Step 3: compute the output weight||β|| ||β|| (1) Where T= [T1,....,TN] The advantages of extreme learning machine algorithm are needs less training time compared to popular Local Binary Pattern ...
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Inverse-free extreme learning machine with optimal information updating
... in learning speed when exposed to datasets with a huge size which were never encountered tens of years ...the extreme learning machine (ELM) is proposed to overcome the slow learning ...
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Regularized minimum class variance extreme learning machine for language recognition
... Inspired by its successful application to classification problems, in this paper, we introduce ELM into spoken language recognition, hoping to open up a new research direction for language recognition community. A new ...
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Rank based Pseudoinverse Computation in Extreme Learning Machine for large Datasets
... called Extreme Learning Machine (ELM) as an alternative to iterative techniques which is a three-step learning algorithm based on universal approximation theorem of ...gradient-based ...
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Impact of Different Random Initializations on Generalization Performance of Extreme Learning Machine
... Extreme learning machine (ELM) [1] is a kind of special single hidden-layer feed-forward neural network (SLFN) in which the input-layer weights and hidden-layer biases are randomly selected and the ...
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Robust algorithm for arrhythmia classification in ECG using extreme learning machine
... classifier, Extreme Learning Machine (ELM) was able to overcome the difficulties of a neural network through a fast learning speed and high performance [12]; the problems that persisted were ...
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A Novel Blind Digital Watermarking Based on SVD and Extreme Learning Machine
... Modification of media and illegal production is a big problem now a days because of free availability of digital media. Protection and securing the digital data is a challenge. An Integer Wavelet transformation (IWt) ...
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Virtual sensing for gearbox condition monitoring based on extreme learning machine
... Abstract. Gearbox, as a critical component to convert speed and torque to maintain machinery normal operation in the industrial processes, has been received and still needs considerable attentions to ensure its reliable ...
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Efficient smile detection by Extreme Learning Machine
... Vector Machine can perform well for the binary classification task, the required time for training and/or prediction may exceed the requirement for real-time ...The Extreme Learning Machine ...
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Performance Comparison of Support Vector Machine, Random Forest, and Extreme Learning Machine for Intrusion Detection
... vector machine (SVM), and other techniques have been used in recent ...Well-known machine learning techniques, namely, SVM, random forest, and extreme learning machine (ELM) are ...
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Regularized Extreme Learning Machine for Large-scale Media Content Analysis
... Extreme Learning Machine has been proposed as an alternative algorithm for Single-hidden Layer Feed- forward Neural (SLFN) networks training [8], towards overcoming the computational bottleneck of ...
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