Feature extraction is a critical issue in many machine learning systems. A number of basic fusion operators have been proposed and studied. This article proposes an evolutionary algorithm, called evolutionary deep fusion method, for searching an optimal combination scheme of different basic fusion operators to fuse multiview features. We apply our proposed method to chemical structure recognition. Our proposed method can directly take images as inputs, and users do not need to transform images to other formats. The experimental results demonstrate that our proposed method can achieve a better performance than those designed by human experts on this real-life problem.

中文翻译：

---

进化深度融合方法及其在化学结构识别中的应用


特征提取是许多机器学习系统中的关键问题。一些基本的融合算子已经被提出并研究。本文提出了一种进化算法，称为进化深度融合方法，用于搜索不同基本融合算子的最佳组合方案来融合多视图特征。我们将我们提出的方法应用于化学结构识别。我们提出的方法可以直接将图像作为输入，用户不需要将图像转换为其他格式。实验结果表明，我们提出的方法可以比人类专家针对这个现实问题设计的方法取得更好的性能。