According to an embodiment of the present invention, a sensor transformation attention network model includes sensors for collecting input signals, attention layers for calculating attention scores for first feature vectors corresponding to input signals, a merge layer for calculating attention values for the attention scores and generating a transformation vector merged by using the attention values and the first feature vectors, and a classification layer for classifying the transformation vector which is merged. Accordingly, the present invention can support multiple modes and/or multiple sensor inputs and attend to a sensor for providing the best signal quality.
SENSOR TRANSFORMATION ATTENTION NETWORKSTAN MODEL