Until now, we have predominantly used two-dimensional convolutional layers. Apart from two-dimensional convolutions, there are one-dimensional and three-dimensional implementations of CNNs, depending upon the type of input data used.

One-dimensional CNNs are widely used for textual data analysis, for example, classifying customer reviews. Unlike images, which are mostly two-dimensional in nature, text data has one-dimensional input data. You can refer to the following example for one-dimensional convolutions, available at https://keras.rstudio.com/articles/examples/imdb_cnn.html here.