标题： 复杂网络与随机神经网络融合用于纹理分析 显示英文标题

标题： Fusion of complex networks and randomized neural networks for texture analysis

摘要： 本文提出了一种基于复网络和随机神经网络融合的高判别性纹理分析方法。 在此方法中，输入图像被建模为复网络，其拓扑特性以及图像像素用于训练随机神经网络，以创建代表纹理深度特征的签名。 获得的结果超过了文献中许多方法的准确性。 此性能表明，我们提出的方法开辟了一个有前景的研究方向，即探索神经网络和复网络在纹理分析领域的协同作用。 显示英文摘要

摘要： This paper presents a high discriminative texture analysis method based on the fusion of complex networks and randomized neural networks. In this approach, the input image is modeled as a complex networks and its topological properties as well as the image pixels are used to train randomized neural networks in order to create a signature that represents the deep characteristics of the texture. The results obtained surpassed the accuracies of many methods available in the literature. This performance demonstrates that our proposed approach opens a promising source of research, which consists of exploring the synergy of neural networks and complex networks in the texture analysis field.