An application of an improved FCOS algorithm in detection and recognition of industrial instruments

Abstract In order to transform the digital workshop, this paper adopts an improved FCOS algorithm to detect the digital display area of industrial instruments and recognize the numbers in the workshop. Specifically, based on the FCOS basic network model, the Balanced Feature Pyramid is combined with FPN to further integrate the feature information and enhance the original feature. The Softer-NMS algorithm instead of the traditional non maximum suppression algorithm, improves the detection accuracy. The experiment shows that the trained network model can be applied to the detection and recognition of industrial instruments, and it has certain validity and accuracy.

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