论文标题
立方盗版器：用于计算图像和音量数据持续同源的软件
Cubical Ripser: Software for computing persistent homology of image and volume data
论文作者
论文摘要
我们介绍了用于计算图像和音量数据的持续同源性的立方盗版器（更确切地说是加权立方体复合物）。据我们所知，Cubical Ripser目前是计算加权立方体络合物持续同源的最快，最有效的程序。我们以图像分析的示例演示了我们的软件，其中持续的同源性和卷积神经网络成功合并。我们的开源实施可在线提供。
We introduce Cubical Ripser for computing persistent homology of image and volume data (more precisely, weighted cubical complexes). To our best knowledge, Cubical Ripser is currently the fastest and the most memory-efficient program for computing persistent homology of weighted cubical complexes. We demonstrate our software with an example of image analysis in which persistent homology and convolutional neural networks are successfully combined. Our open-source implementation is available online.
