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The detection of typical targets under the background of land war

This paper investigates whether advanced neural network techniques can be applied to the detection and identification of typical targets in the context of land warfare. We collected 13 typical targets and built a detection data set. Based on the Faster R-CNN framework, we improve the detection accuracy by two ways. First, we design a neural network model with strong local modeling capabilities. Second, we combine middle layers and the last layer of feature maps as the detection features to enhance the detection ability and improve the detection accuracy.