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- 2018
混合PSO优化卷积神经网络结构和参数
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Abstract:
为了使卷积神经网络在非经验指导下自动寻得最优连接，并提高其参数优化效率，提出用粒子群优化卷积网络参数，并用离散粒子群优化卷积网络特征图之间连接结构的新方法。先使用粒子群优化所有权值，再采用离散粒子群优化降采样层和卷积层之间特征图连接结构。将该方法用于MNIST数据集和CIFAR-10数据集，实验结果表明，相比其他连接结构的卷积神经网络和其他识别方法，该方法可以有效实现网络结构及参数的优化，加速网络收敛并提高识别准确比。
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