Survey on evolutionary deep learning: Principles, algorithms, applications, and open issues
Over recent years, there has been a rapid development of deep learning (DL) in both
industry and academia fields. However, finding the optimal hyperparameters of a DL model …
industry and academia fields. However, finding the optimal hyperparameters of a DL model …
Automatic design of machine learning via evolutionary computation: A survey
Abstract Machine learning (ML), as the most promising paradigm to discover deep
knowledge from data, has been widely applied to practical applications, such as …
knowledge from data, has been widely applied to practical applications, such as …
Not just select samples, but exploration: Genetic programming aided remote sensing target detection under deep learning
The data of target detection in remote sensing images are diverse, and the detection results
of some categories with a small number of samples are poor. In order to solve this problem …
of some categories with a small number of samples are poor. In order to solve this problem …
Convolutional neural network pruning based on multi-objective feature map selection for image classification
Deep convolutional neural networks (CNNs) are widely used for image classification. Deep
CNNs often require a large memory and abundant computation resources, limiting their …
CNNs often require a large memory and abundant computation resources, limiting their …
Artificial intelligence for the management of servitization 5.0
B Nicoletti, A Appolloni - Sustainability, 2023 - mdpi.com
Purpose—The sale of physical products has been manufacturing companies' main revenue
source. A trend is known as servitization for earning revenue comes from services. With the …
source. A trend is known as servitization for earning revenue comes from services. With the …
Particle swarm optimization for efficiently evolving deep convolutional neural networks using an autoencoder-based encoding strategy
Deep convolutional neural networks (DCNNs) have achieved surpassing success in the
field of computer vision, and a number of elaborately designed networks refresh the …
field of computer vision, and a number of elaborately designed networks refresh the …
Research on threshold segmentation method of two-dimensional Otsu image based on improved sparrow search algorithm
Y Du, H Yuan, K Jia, F Li - IEEE Access, 2023 - ieeexplore.ieee.org
Aiming at the issues of complex calculation and low accuracy of two-dimensional (2D) Otsu
segmentation images, an image threshold segmentation means of 2D Otsu ground on a …
segmentation images, an image threshold segmentation means of 2D Otsu ground on a …
EST-NAS: An evolutionary strategy with gradient descent for neural architecture search
Using weight-sharing and continuous relaxation strategies, the gradient descent-based
differential architecture search has achieved great success in automatically designing …
differential architecture search has achieved great success in automatically designing …
Evolutionary architecture search for generative adversarial networks based on weight sharing
Generative adversarial networks (GANs) are a powerful generative technique but frequently
face challenges with training stability. Network architecture plays a significant role in …
face challenges with training stability. Network architecture plays a significant role in …
Genetic programming-based evolutionary deep learning for data-efficient image classification
Data-efficient image classification is a challenging task that aims to solve image
classification using small training data. Neural network-based deep learning methods are …
classification using small training data. Neural network-based deep learning methods are …