In recent years, research in applying optimization approaches in the automatic design of
deep neural networks has become increasingly popular. Although various approaches have …

Computer vision is one of the most frontier technologies in computer science. It is used to
build artificial systems to extract valuable information from images and has a broad range of …

The cloud computing paradigm, as a novel computing resources delivery platform, has
significantly impacted society with the concept of on-demand resource utilization through …

Feature selection and hyper-parameters optimization (tuning) are two of the most important
and challenging tasks in machine learning. To achieve satisfying performance, every …

Gliomas belong to the group of the most frequent types of brain tumors. For this specific type
of brain tumors, in its beginning stages, it is extremely complex to get the exact diagnosis …

Artificial neural networks are very powerful machine learning techniques and they are
capable to solve complex problems. In the artificial neural network, one of the most difficult …

Convolutional neural networks have a broad spectrum of practical applications in computer
vision. Currently, much of the data come from images, and it is crucial to have an efficient …

Cloud computing technology refers to on-demand access to services, applications, and
infrastructure that runs on a distributed network utilizing virtualized resources. In the cloud …

This paper presents an approach to design convolutional neural network architectures,
using the particle swarm optimization algorithm. The adjustment of the hyper-parameters …

The salp swarm algorithm is one of the novel swarm intelligence metaheuristics. The work
proposed in this paper provides further improvements of the salp swarm algorithm, that have …