ConvLSTM2D层的应用 [英] Application of ConvLSTM2D layers

问题描述

我在github上浏览了一些代码，并注意到Keras中的一个名为ConvLSTM2D的层. Keras文档指出It is similar to an LSTM layer, but the input transformations and recurrent transformations are both convolutional..

I was going through some codes over github and noticed a layer called ConvLSTM2D in Keras. The Keras documentations states that It is similar to an LSTM layer, but the input transformations and recurrent transformations are both convolutional..

我想知道该层的实际应用是什么.我对NLP很熟悉，但是我还没有看到这一层的使用.

I am wondering what will be the practical application of this layer. I am familiar with NLP and I haven't seen this layer being used.

机器学习/深度学习的哪个领域使用此层?

Which area of Machine Learning / Deep Learning make use of this layer.?

推荐答案

ConvLSTM2D图层用于时空问题的计算机视觉问题，即您要提取空间特征以及时间相关性的地方. 请参阅ConvLSTM论文

ConvLSTM2D Layer is used in computer vision problems for spatiotemporal problems i.e where you want to extract the spatial features as well as the correlation in time. Refer to the ConvLSTM paper

卷积LSTM网络:一种用于降水临近预报的机器学习方法"

它说明完全连接的LSTM可以捕获时间相关性，但不对空间数据进行编码.这就是为什么他们提出了一个模型，其中状态到状态的输入和状态到状态的转换是卷积的

It explains that the fully-connected LSTM can capture the temporal correlation but do not encode the spatial data. Thats why they propose a model where the input to state and state to state transitions are convolutional

我可以找到一些论文，其中ConvLSTM是自然视频序列预测，手势识别和视频分类模型的一部分，即基本上是我们想要学习时空数据的地方

I could find papers where ConvLSTM was a part of the model for natural video sequence prediction, gesture recognition and video classification i.e basically where we want to learn spatial and temporal data

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