Application of meta-heuristic algorithms for training neural networks and deep learning architectures: A comprehensive review
The learning process and hyper-parameter optimization of artificial neural networks (ANNs)
and deep learning (DL) architectures is considered one of the most challenging machine …
and deep learning (DL) architectures is considered one of the most challenging machine …
A comprehensive survey on optimizing deep learning models by metaheuristics
Deep neural networks (DNNs), which are extensions of artificial neural networks, can learn
higher levels of feature hierarchy established by lower level features by transforming the raw …
higher levels of feature hierarchy established by lower level features by transforming the raw …
A survey of swarm and evolutionary computing approaches for deep learning
Deep learning (DL) has become an important machine learning approach that has been
widely successful in many applications. Currently, DL is one of the best methods of …
widely successful in many applications. Currently, DL is one of the best methods of …
Improved deep convolutional neural networks using chimp optimization algorithm for Covid19 diagnosis from the X-ray images
Abstract Applying Deep Learning (DL) in radiological images (ie, chest X-rays) is emerging
because of the necessity of having accurate and fast COVID-19 detectors. Deep …
because of the necessity of having accurate and fast COVID-19 detectors. Deep …
Soft-tempering deep belief networks parameters through genetic programming
Deep neural networks have been widely fostered throughout the last years, primarily on
account of their outstanding performance in various tasks, such as objects, images, faces …
account of their outstanding performance in various tasks, such as objects, images, faces …
Metaheuristic algorithms for convolution neural network
A typical modern optimization technique is usually either heuristic or metaheuristic. This
technique has managed to solve some optimization problems in the research area of …
technique has managed to solve some optimization problems in the research area of …
Evolving deep learning convolutional neural networks for early COVID-19 detection in chest X-ray images
This article proposes a framework that automatically designs classifiers for the early
detection of COVID-19 from chest X-ray images. To do this, our approach repeatedly makes …
detection of COVID-19 from chest X-ray images. To do this, our approach repeatedly makes …
Optimization of convolutional neural network using the linearly decreasing weight particle swarm optimization
T Serizawa, H Fujita - arxiv preprint arxiv:2001.05670, 2020 - arxiv.org
Convolutional neural network (CNN) is one of the most frequently used deep learning
techniques. Various forms of models have been proposed and im-proved for learning at …
techniques. Various forms of models have been proposed and im-proved for learning at …
Fine-tuned residual network-based features with latent variable support vector machine-based optimal scene classification model for unmanned aerial vehicles
In recent days, unmanned aerial vehicles (UAVs) becomes more familiar because of its
versatility, automation abilities, and low cost. Dynamic scene classification gained significant …
versatility, automation abilities, and low cost. Dynamic scene classification gained significant …