论文标题

卷积神经网络中心电图的表示问题

Problems of representation of electrocardiograms in convolutional neural networks

论文作者

Sereda, Iana, Alekseev, Sergey, Koneva, Aleksandra, Khorkin, Alexey, Osipov, Grigory

论文摘要

以心电图为例,我们证明了通过标准卷积网络对一维重复模式进行建模时出现的特征问题。我们表明这些问题本质上是系统性的。它们是由于卷积网络如何与复合对象一起工作,而复合对象的一部分不是严格固定的,但具有明显的机动性。我们还展示了与深网中泛化有关的一些违反直觉效应。

Using electrocardiograms as an example, we demonstrate the characteristic problems that arise when modeling one-dimensional signals containing inaccurate repeating pattern by means of standard convolutional networks. We show that these problems are systemic in nature. They are due to how convolutional networks work with composite objects, parts of which are not fixed rigidly, but have significant mobility. We also demonstrate some counterintuitive effects related to generalization in deep networks.

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