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Cell Coverage Estimation Based on Structured Random Forests Edge Detection and Boundary Tracking

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DOI: 10.23977/AICT2020003

Author(s)

Xiaohu Liu

Corresponding Author

ABSTRACT

To estimate the cell coverage accurately and effectively, an approach based on the structured random forests with mutual information and boundary tracking is proposed. And with the structured random forest, which is improved with mutual information to enhance the mapping function from the structured information to discrete labels, the salient and sematic edges are detected. On the basis of detected edges, the cell contours are found using boundary tracking algorithm. And the experiments imply the effective of the proposed method.

KEYWORDS

Edge Detection; Boundary Tracking Algorithm; Structured Random Forests

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