Anomalies are rare observations (eg, data records or events) that deviate significantly from
the others in the sample. Over the past few decades, research on anomaly mining has …

With the development of remote sensing technology, the application of hyperspectral images
is becoming more and more widespread. The accurate classification of ground features …

This letter identifies original independent works in the domain of randomization-based
feedforward neural networks. In the most common approach, only the output layer weights …

Neural networks have been successfully employed in various domains such as
classification, regression and clustering, etc. Generally, the back propagation (BP) based …

In this paper, we propose deep learning frameworks based on the randomized neural
network. Inspired by the principles of Random Vector Functional Link (RVFL) network, we …

Vehicular ad hoc networks (VANETs) and the services they support are an essential part of
intelligent transportation. Through physical technologies, applications, protocols, and …

This paper proposes a three-stage online deep learning model for time series based on the
ensemble deep random vector functional link (edRVFL). The edRVFL stacks multiple …

Анотація The work is devoted to the study of pattern recognition features of industrial parts
in individual fasteners' forms. The main types of neural network architectures and their …

Extreme learning machine (ELM), which can be viewed as a variant of Random Vector
Functional Link (RVFL) network without the input–output direct connections, has been …

Autoencoder (AE) is an unsupervised neural network framework for efficient and effective
feature extraction. Most AE-based methods do not consider spatial information and band …