Computer Area Localization Algorithm Based on FCN

Abstract

Computer area localization algorithms are an important area of research aimed at accurately determining object locations. However, traditional regional localization algorithms have certain limitations in the face of complex scenes and changing environments. To overcome these problems, this paper proposes a region localization algorithm based on a FCN. Through experimental evaluation and data analysis, this paper finds that the regional localization algorithm based on FCN has obvious advantages over traditional algorithms. Experimental results show that the algorithm shows better performance in terms of accuracy rate and error distance. Specifically, the algorithm based on the FCN has achieved a positioning accuracy of 70%, which is much higher than the 30% of the traditional algorithm. In this paper, its superiority in localization tasks is verified through experimental evaluation and data analysis. The algorithm not only improves the accuracy and precision of positioning, but also has strong robustness and generalization ability. This provides a more accurate and reliable positioning solution for practical application scenarios, and provides strong support for the development of autonomous driving, intelligent navigation and other fields.