Semantic Segmentation Based on Improved Robinson Operator

Authors

  • Xiaoshuo Jia
  • Zhihui Li

DOI:

https://doi.org/10.54097/ajst.v2i3.1433

Keywords:

Semantic segmentation, Residual structure, Pooling layer, Lightweigth model, Robinson Operator.

Abstract

Classical pixel-level semantic segmentation methods are easily affected by factors such as environment and pixel values, resulting in low accuracy of their methods. Therefore, in order to improve the accuracy of pixel-level semantic segmentation under practical conditions, this paper designs a lightweight network based on the nonlinear characteristics of residual structure and the characteristics of optimized edge operators. The experimental results show that the designed lightweight residual network can effectively improve the accuracy by about 2% compared with the traditional residual network, and the model size is reduced from the original 40.2MB to 18.9MB.

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Published

26 August 2022

How to Cite

Jia, X., & Li, Z. (2022). Semantic Segmentation Based on Improved Robinson Operator. Academic Journal of Science and Technology, 2(3), 1–3. https://doi.org/10.54097/ajst.v2i3.1433

Issue

Section

Articles