Apparatus and method for anomaly detection

Abstract

An anomaly detection method and apparatus are provided using an attention mechanism or based on an artificial neural network for minimizing computational cost. In an embodiment, the anomaly detection method may include entering, by a detection unit, input data into a detection network; generating, by the detection network, an attention map and output data through a plurality of operations in which a plurality of layer weights are applied to the input data; generating, by the detection unit, an attention map by overlapping the attention map with the input data when an attention region having an attention value greater than or equal to a predetermined threshold exists in the attention map; detecting, by the detection unit, whether the input data is normal or abnormal according to the output data; and outputting, by the detection unit, the detection map and an anomaly detection result indicating whether the input data is normal or abnormal.