Results 1 to 10 of about 605,541 (277)

R-ELMNet: Regularized extreme learning machine network

Neural Networks, 2020
Principal component analysis network (PCANet), as an unsupervised shallow network, demonstrates noticeable effectiveness on datasets of various volumes. It carries a two-layer convolution with PCA as filter learning method, followed by a block-wise histogram post-processing stage. Following the structure of PCANet, extreme learning machine auto-encoder
Guanghao Zhang, Yue Li, Dongshun Cui, Shangbo Mao, Guang-Bin Huang   +4 more
openaire   +4 more sources

Globality-Locality Preserving Maximum Variance Extreme Learning Machine

Complexity, 2019
An extreme learning machine (ELM) is a useful technique for machine learning; however, the existing extreme learning machine methods cannot exploit the geometric structure information or discriminate information of the data space well.
Yonghe Chu, Hongfei Lin, Liang Yang, Yufeng Diao, Dongyu Zhang, Shaowu Zhang, Xiaochao Fan, Chen Shen, Deqin Yan   +8 more
doaj   +1 more source

Інтелектуалізація процесу діагностування онкопатологій [PDF]

, 2013
Одним із ефективних способів вирішення проблеми боротьби з онкозахворюваннями є інтелектуалізація процесу діагностування. При цитуванні документа, використовуйте посилання http://essuir.sumdu.edu.ua/handle/123456789/31771Under extreme intellectual ...
Дрофа, В.О.
core  

Adaptive Safe Semi-Supervised Extreme Machine Learning

IEEE Access, 2019
Semi-supervised learning (SSL) based on manifold regularization (MR) is an excellent learning framework. However, the performance of SSL heavily depends on the construction of manifold graph and the safety degrees of unlabeled samples.
Jun Ma, Chao Yuan
doaj   +1 more source

Improving Multi-Instance Multi-Label Learning by Extreme Learning Machine

Applied Sciences, 2016
Multi-instance multi-label learning is a learning framework, where every object is represented by a bag of instances and associated with multiple labels simultaneously.
Ying Yin, Yuhai Zhao, Chengguang Li, Bin Zhang   +3 more
doaj   +1 more source

A Novel Data Fusion Strategy Based on Extreme Learning Machine Optimized by Bat Algorithm for Mobile Heterogeneous Wireless Sensor Networks

IEEE Access, 2020
In order to effectively reduce the redundant information transmission in the network, a data fusion algorithm based on extreme learning machine optimized by bat algorithm for mobile heterogeneous wireless sensor networks is proposed.
Li Cao, Yong Cai, Yinggao Yue, Shaotang Cai, Bo Hang   +4 more
doaj   +1 more source

Inverse kinematics solution for robotic manipulator based on extreme learning machine and sequential mutation genetic algorithm

International Journal of Advanced Robotic Systems, 2018
This article presents an intelligent algorithm based on extreme learning machine and sequential mutation genetic algorithm to determine the inverse kinematics solutions of a robotic manipulator with six degrees of freedom.
Zhiyu Zhou, Hanxuan Guo, Yaming Wang, Zefei Zhu, Jiang Wu, Xiangqi Liu   +5 more
doaj   +1 more source

Extreme learning machines for feature learning [PDF]

, 2020
Neural Networks (NN) map input data to desired output data in image processing, time series prediction and data analytics. The commonly used variant of NN is Single Layer Feed forward Neural network (SLFN) due to its simple network architecture and universal approximation capability.
openaire   +2 more sources

Local Coupled Extreme Learning Machine Based on Particle Swarm Optimization

Algorithms, 2018
We developed a new method of intelligent optimum strategy for a local coupled extreme learning machine (LC-ELM). In this method, both the weights and biases between the input layer and the hidden layer, as well as the addresses and radiuses in the local ...
Hongli Guo, Bin Li, Wei Li, Fengjuan Qiao, Xuewen Rong, Yibin Li   +5 more
doaj   +1 more source

Comparative Analysis of Artificial Neural Networks and Extreme Learning Machine Techniques for Breast Cancer Diagnosis [PDF]

Liaquat National Journal of Cancer Care
Background: Breast cancer is the second dangerous disease that causes death in women. Early detection can reduce mortality rates by 40% or more. The procedures to be carried out in this process create extra labor and financial costs for both the patient
Ulku Veranyurt, Betul Akalin, Arzu Irban, Ozan Veranyurt   +3 more
doaj   +1 more source