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Completely automated CNN architecture design based on blocks
The performance of convolutional neural networks (CNNs) highly relies on their
architectures. In order to design a CNN with promising performance, extensive expertise in …
architectures. In order to design a CNN with promising performance, extensive expertise in …
A self-adaptive mutation neural architecture search algorithm based on blocks
Recently, convolutional neural networks (CNNs) have achieved great success in the field of
artificial intelligence, including speech recognition, image recognition, and natural language …
artificial intelligence, including speech recognition, image recognition, and natural language …
Spontaneous evolution of modularity and network motifs
Biological networks have an inherent simplicity: they are modular with a design that can be
separated into units that perform almost independently. Furthermore, they show reuse of …
separated into units that perform almost independently. Furthermore, they show reuse of …
Efficient decoupling-assisted evolutionary/metaheuristic framework for expensive reliability-based design optimization problems
Reliability-based design optimization (RBDO) algorithm is to minimize the objective under
the probabilistic factors. While gradient-based and classical evolutionary RBDO algorithms …
the probabilistic factors. While gradient-based and classical evolutionary RBDO algorithms …
Genetic U-Net: automatically designed deep networks for retinal vessel segmentation using a genetic algorithm
Recently, many methods based on hand-designed convolutional neural networks (CNNs)
have achieved promising results in automatic retinal vessel segmentation. However, these …
have achieved promising results in automatic retinal vessel segmentation. However, these …
Evolving block-based convolutional neural network for hyperspectral image classification
Deep convolutional neural network (CNN) shows excellent effectiveness on hyperspectral
image (HSI) classification. However, the architecture design of CNN requires abundant …
image (HSI) classification. However, the architecture design of CNN requires abundant …
Design of a hybrid energy management system using designed rule‐based control strategy and genetic algorithm for the series‐parallel plug‐in hybrid electric vehicle
Electric vehicle (EV) is considered as a critical requirement to the future development of
transportation. However, the battery performance in terms of power density and energy …
transportation. However, the battery performance in terms of power density and energy …
Multiobjective genetic algorithms applied to solve optimization problems
In this paper, we discuss multiobjective optimization problems solved by evolutionary
algorithms. We present the nondominated sorting genetic algorithm (NSGA) to solve this …
algorithms. We present the nondominated sorting genetic algorithm (NSGA) to solve this …
[HTML][HTML] Evaluating genetic algorithms through the approximability hierarchy
Optimization problems frequently appear in any scientific domain. Most of the times, the
corresponding decision problem turns out to be NP-hard, and in these cases genetic …
corresponding decision problem turns out to be NP-hard, and in these cases genetic …
Hermite functions and uncertainty principles for the Fourier and the windowed Fourier transforms
We extend an uncertainty principle due to Beurling into a characterization of Hermite
functions. More precisely, all functions f on Rd which may be written as P (x) exp (−〈 Ax, x〉) …
functions. More precisely, all functions f on Rd which may be written as P (x) exp (−〈 Ax, x〉) …