Spatiotemporal data, or data with spatial and temporal qualities, are a common occurrence. Examples include videos, as well as sequences of image-like data, such as spectrograms.
Convolutional Neural Networks (CNNs) are particularly suited for finding spatial patterns. Recurrent Neural Networks (RNNs), on the other hand, are particularly suited for finding temporal patterns. These two, in combination with Multilayer Perceptrons, can be effective for classifying spatiotemporal inputs.