翻译：MAE-NAS是一种低成本的定制模型其基本思想为将深度网络视为连续状态空间的信息系统并最大化该信息系统的熵值。在网络建模过程中将网络F的拓扑结构抽象为图G=VE顶点V表示特征边E表示各种算子熵HS衡量整个信息系统F包含的总信息量因为在目标检测的特征提取部分只关注网络的表达能力所以这里只计算顶点中的信息量。

MAE-NAS is a low-cost customized model that treats deep networks as information systems with continuous state space and maximizes the entropy of the information system. In the process of network modeling, the topological structure of network F is abstracted as a graph G=(V,E), where vertices V represent features and edges E represent various operators. The entropy H(S) measures the total amount of information contained in the entire information system F. Since only the expressive power of the network is concerned in the feature extraction part of object detection, only the information in the vertices is calculated here