Metaheuristics for bilevel optimization: A comprehensive review
A bilevel programming model represents the relationship in a specific decision process that
involves decisions within a hierarchical structure of two levels. The upper-level problem is …
involves decisions within a hierarchical structure of two levels. The upper-level problem is …
Exploring the advancements and future research directions of artificial neural networks: a text mining approach
Artificial Neural Networks (ANNs) are machine learning algorithms inspired by the structure
and function of the human brain. Their popularity has increased in recent years due to their …
and function of the human brain. Their popularity has increased in recent years due to their …
Two-Phase Evolutionary Convolutional Neural Network Architecture Search for Medical Image Classification
Recently, convolutional neural networks (CNNs) have shown promising achievements in
various computer vision tasks. However, designing a CNN model architecture necessitates a …
various computer vision tasks. However, designing a CNN model architecture necessitates a …
Advancing Sustainable COVID-19 Diagnosis: Integrating Artificial Intelligence with Bioinformatics in Chest X-ray Analysis
Responding to the critical health crisis triggered by respiratory illnesses, notably COVID-19,
this study introduces an innovative and resource-conscious methodology for analyzing chest …
this study introduces an innovative and resource-conscious methodology for analyzing chest …
Topology optimization search of deep convolution neural networks for CT and X-ray image classification
Covid-19 is a disease that can lead to pneumonia, respiratory syndrome, septic shock,
multiple organ failure, and death. This pandemic is viewed as a critical component of the …
multiple organ failure, and death. This pandemic is viewed as a critical component of the …
Universal Binary Neural Networks Design by Improved Differentiable Neural Architecture Search
Binary Neural Networks (BNNs) using 1-bit weights and activations are emerging as a
promising approach for mobile devices and edge computing platforms. Concurrently …
promising approach for mobile devices and edge computing platforms. Concurrently …
Traffic disturbance mining and feedforward neural network to enhance the immune network control performance
Traffic disturbance in urban cities challenges the most advanced traffic signal control
systems (TSCS). The challenge is mainly related to the capability of TSCS to ensure a quick …
systems (TSCS). The challenge is mainly related to the capability of TSCS to ensure a quick …
Design and compression study for convolutional neural networks based on evolutionary optimization for thoracic X-Ray image classification
Computer Vision has lately shown progress in addressing a variety of complex health care
difficulties and has the potential to aid in the battle against certain lung illnesses, including …
difficulties and has the potential to aid in the battle against certain lung illnesses, including …
Optimizing Deep Learning for Computer-Aided Diagnosis of Lung Diseases: An Automated Method Combining Evolutionary Algorithm and Transfer Learning
Abstract Recent advancements in Computer Vision have opened up new opportunities for
addressing complex healthcare challenges, particularly in the area of lung disease …
addressing complex healthcare challenges, particularly in the area of lung disease …
Augmented Reality Coupled with Deep Convolution Neural Networks to Enhance Archaeological Sites Experience
L Ajili, H Louati, F Ben Ameur - New Trends in Intelligent …, 2023 - ebooks.iospress.nl
Cultural sites tend to revive themselves through digitization and try to keep pace with
modern technology in order to meet the growing needs of the public. In fact, different cultural …
modern technology in order to meet the growing needs of the public. In fact, different cultural …