Algorithm 1 Spatio-temporal Feature Fusion Algorithm

Input: INP1, INP2 Output: Spatio-temporal fusion feature

Conduct regular processing. Keep the chronological order of the entire sequence, and use one-dimensional convolutional layer to extract local spatial features to obtain spatial information. Extract local spatial extreme values by one-dimensional pooling layer to obtain a multi-dimensional spatiotemporal feature map Learn the characteristics of the data sequence over time through LSTM. Splice the above two features to get the final spatiotemporal fusion feature.