883 citations · 2.2k across the 58 of their papers we have counts for
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Automatically Evolving CNN Architectures Based on Blocks
Yanan Sun, Bing Xue, Mengjie Zhang +1
The performance of Convolutional Neural Networks (CNNs) highly relies on their architectures. In order to design a CNN with promising performance, extended expertise in both CNNs a…
A Hybrid Differential Evolution Approach to Designing Deep Convolutional Neural Networks for Image Classification
Bin Wang, Yanan Sun, Bing Xue +1
Convolutional Neural Networks (CNNs) have demonstrated their superiority in image classification, and evolutionary computation (EC) methods have recently been surging to automatica…
Automatically designing CNN architectures using genetic algorithm for image classification
Yanan Sun, Bing Xue, Mengjie Zhang +1
Convolutional Neural Networks (CNNs) have gained a remarkable success on many image classification tasks in recent years. However, the performance of CNNs highly relies upon their…
Generating Redundant Features with Unsupervised Multi-Tree Genetic Programming
Andrew Lensen, Bing Xue, Mengjie Zhang
Recently, feature selection has become an increasingly important area of research due to the surge in high-dimensional datasets in all areas of modern life. A plethora of feature s…
Evolving Deep Convolutional Neural Networks by Variable-length Particle Swarm Optimization for Image Classification
Bin Wang, Yanan Sun, Bing Xue +1
Convolutional neural networks (CNNs) are one of the most effective deep learning methods to solve image classification problems, but the best architecture of a CNN to solve a speci…