A review on weight initialization strategies for neural networks

MV Narkhede, PP Bartakke, MS Sutaone - Artificial intelligence review, 2022‏ - Springer
Over the past few years, neural networks have exhibited remarkable results for various
applications in machine learning and computer vision. Weight initialization is a significant …

A review on neural networks with random weights

W Cao, X Wang, Z Ming, J Gao - Neurocomputing, 2018‏ - Elsevier
In big data fields, with increasing computing capability, artificial neural networks have shown
great strength in solving data classification and regression problems. The traditional training …

A hybrid feature extraction method with regularized extreme learning machine for brain tumor classification

A Gumaei, MM Hassan, MR Hassan, A Alelaiwi… - IEEE …, 2019‏ - ieeexplore.ieee.org
Brain cancer classification is an important step that depends on the physician's knowledge
and experience. An automated tumor classification system is very essential to support …

A review of machine learning for near-infrared spectroscopy

W Zhang, LC Kasun, QJ Wang, Y Zheng, Z Lin - Sensors, 2022‏ - mdpi.com
The analysis of infrared spectroscopy of substances is a non-invasive measurement
technique that can be used in analytics. Although the main objective of this study is to …

Non-iterative and fast deep learning: Multilayer extreme learning machines

J Zhang, Y Li, W **ao, Z Zhang - Journal of the Franklin Institute, 2020‏ - Elsevier
In the past decade, deep learning techniques have powered many aspects of our daily life,
and drawn ever-increasing research interests. However, conventional deep learning …

What are extreme learning machines? Filling the gap between Frank Rosenblatt's dream and John von Neumann's puzzle

GB Huang - Cognitive Computation, 2015‏ - Springer
The emergent machine learning technique—extreme learning machines (ELMs)—has
become a hot area of research over the past years, which is attributed to the growing …

Deep learning based brain tumor classification and detection system

A Ari, D Hanbay - Turkish Journal of Electrical Engineering …, 2018‏ - journals.tubitak.gov.tr
The brain cancer treatment process depends on the physician's experience and knowledge.
For this reason, using an automated tumor detection system is extremely important to aid …

An efficient method for traffic sign recognition based on extreme learning machine

Z Huang, Y Yu, J Gu, H Liu - IEEE transactions on cybernetics, 2016‏ - ieeexplore.ieee.org
This paper proposes a computationally efficient method for traffic sign recognition (TSR).
This proposed method consists of two modules:(1) extraction of histogram of oriented …

High-performance extreme learning machines: a complete toolbox for big data applications

A Akusok, KM Björk, Y Miche, A Lendasse - IEEE Access, 2015‏ - ieeexplore.ieee.org
This paper presents a complete approach to a successful utilization of a high-performance
extreme learning machines (ELMs) Toolbox for Big Data. It summarizes recent advantages …

Dimension reduction with extreme learning machine

LLC Kasun, Y Yang, GB Huang… - IEEE transactions on …, 2016‏ - ieeexplore.ieee.org
Data may often contain noise or irrelevant information, which negatively affect the
generalization capability of machine learning algorithms. The objective of dimension …