Multi-level thresholding image segmentation based on improved slime mould algorithm and symmetric cross-entropy

HIGHLIGHTS

  • who: Yuanyuan Jiang and collaborators from the School of Electrical and Information Engineering, Anhui University of Science and Technology, Huainan, China have published the paper: Multi-Level Thresholding Image Segmentation Based on Improved Slime Mould Algorithm and Symmetric Cross-Entropy, in the Journal: Entropy 2023, 178 of /2023/
  • what: The authors propose an improved slime mould algorithm, called ISMA, for the multilevel thresholding image segmentation task.
  • how: This paper introduces a new adaptive probability threshold to cause the slime mould to select the appropriate predation strategy for the current population 5 of 29 . . .

     

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