一种结构自适应免疫抗体竞争网络的非监督图像分割

提出一种新的结构自适应免疫抗体竞争网络，无须预先设定聚类数目，实现了完全非监督的图像分割．基于自组织特征映射神经网络的基本概念，提出一个新的免疫抗体邻域概念，增强了网络的鲁棒性．根据大脑皮层长期记忆的形成原理提出一个长期记忆因子，提高了算法收敛的速度．为了抑制噪声抗原对抗体网络的影响，提出3种抗体死亡操作．以上这些改进措施可使生成的抗体网络更好地反映抗原的分布特征，得到自适应的网络结构．将此算法用于合成纹理图像、遥感图像和合成孔径雷达图像的分割，都取得了较好的分割结果．

Unsupervised image segmentation using an immune antibody competitive network

This paper proposes a fully unsupervised image segmentation algorithm by using a novel structural adaptation artificial immune antibody competitive network without a predefined number of clustering.Based on the basic conception of self organizing feature map,a new immune antibody neighborhood is presented to enhance the robustness of the network,and inspired by the long-term memory in cerebral cortices,a long-term memory coefficient is introduced into the network to improve the convergence speed of the algo...