Unravelling an optical extreme learning machine [PDF]
EPJ Web of Conferences, 2022 Extreme learning machines (ELMs) are a versatile machine learning technique that can be seamlessly implemented with optical systems. In short, they can be described as a network of hidden neurons with random fixed weights and biases, that generate a ...
Silva Duarte +4 more
doaj +1 more source
Efficient smile detection by Extreme Learning Machine [PDF]
, 2015 Smile detection is a specialized task in facial expression analysis with applications such as photo selection, user experience analysis, and patient monitoring.
An, L, Bhanu, B, Yang, S
core +1 more source
SAFA : a semi-asynchronous protocol for fast federated learning with low overhead [PDF]
, 2020 Federated learning (FL) has attracted increasing attention as a promising approach to driving a vast number of end devices with artificial intelligence.
He, Ligang +5 more
core +2 more sources
Experimenting with Extreme Learning Machine for Biomedical Image Classification
Applied Sciences, 2023 Currently, deep learning networks, with particular regard to convolutional neural network models, are typically exploited for biomedical image classification.
Francesco Mercaldo +4 more
doaj +1 more source
Linear vs Nonlinear Extreme Learning Machine for Spectral-Spatial Classification of Hyperspectral Image [PDF]
, 2017 As a new machine learning approach, extreme learning machine (ELM) has received wide attentions due to its good performances. However, when directly applied to the hyperspectral image (HSI) classification, the recognition rate is too low. This is because
Cao, Faxian +4 more
core +3 more sources
Haptic identification by ELM-controlled uncertain manipulator [PDF]
, 2017 This paper presents an extreme learning machine (ELM) based control scheme for uncertain robot manipulators to perform haptic identification. ELM is used to compensate for the unknown nonlinearity in the manipulator dynamics.
Cheng, Hong +4 more
core +1 more source
Development and research of a neural network alternate incremental learning algorithm
Компьютерная оптика, 2023 In this paper, the relevance of developing methods and algorithms for neural network incremental learning is shown. Families of incremental learning techniques are presented. A possibility of using the extreme learning machine for incremental learning is
A.A. Orlov, E.S. Abramova
doaj +1 more source
Research on an improved lp-RWMKE-ELM fault diagnosis model
工程科学学报, 2022 As the service time of military equipment increases, equipment failure data is continuously accumulated during events such as routine maintenance, training, and combat readiness exercises, and the data presented is often imbalanced to varying degrees and
Xing LIU +3 more
doaj +1 more source
A Novel Fault Diagnosis Method for Motor Bearing Based on DTCWT and AFSO-KELM
Shock and Vibration, 2021 Aiming at the defects of wavelet transform-based feature extraction and extreme learning machine-based classification, a novel fault diagnosis method for motor bearing, based on dual tree complex wavelet transform and artificial fish swarm optimization ...
Yan Lu, Peijiang Li
doaj +1 more source
FORECASTING OF CURRENCY CIRCULATION IN INDONESIA USING HYBRID EXTREME LEARNING MACHINE
Barekeng, 2022 Forecasting currency circulation, including inflow and outflow, is one of Bank Indonesia's strategies to maintain the Rupiah value's stability. The characteristic of inflow and outflow data is that they have seasonal variations.
Mujiati Dwi Kartikasari
doaj +1 more source