标题： 学习通过多模光纤观察 显示英文标题

标题： Learning to see through multimode fibers

摘要： 我们使用深度神经网络（DNNs）来分类和重建通过多模光纤（MMF）传播图像后产生的散斑图案的强度的大数据库中的手写数字。 通过长度高达1公里的光纤传输的图像被恢复了。 网络识别因光纤长度而退化的输入的能力，但如果神经网络被训练为首先重建图像然后再进行分类，而不是直接从散斑强度进行分类，那么性能可以得到提升。 显示英文摘要

摘要： We use Deep Neural Networks (DNNs) to classify and reconstruct a large database of handwritten digits from the intensity of the speckle patterns that result after the images propagated through multimode fibers (MMF). Images transmitted through fibers with up to 1km length were recovered. The ability of the network to recognize the input degraded with fiber length but the performance could be enhanced if the neural networks were trained to first reconstruct the image and then classify it rather than classify it directly from the speckle intensity.