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Artemisinin Optimization based on Malaria Therapy: Algorithm and Applications to Medical Image Segmentation

AO

66 papers tagged archive 2025-07-28

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

This study proposes an efficient metaheuristic algorithm called the Artemisinin Optimization (AO) algorithm. This algorithm draws inspiration from the process of artemisinin medicine therapy for malaria, which involves the comprehensive eradication of malarial parasites within the human body. AO comprises three optimization stages: a comprehensive eliminations phase simulating global exploration, a local clearance phase for local exploitation, and a post-consolidation phase to enhance the algorithm's ability to escape local optima. In the experimental, this paper conducts a qualitative analysis experiment on the AO, explaining its characteristics in searching for the optimal solution. Subsequently, AO is then tested on the classical IEEE CEC 2014, and the latest IEEE CEC 2022 benchmark function sets to assess its adaptability. Comparative analyses are conducted against eight well-established algorithms and eight high-performance improved algorithms. Statistical analyses of convergence curves and qualitative metrics revealed AO's robust competitiveness. Lastly, the AO is incorporated into breast cancer pathology image segmentation applications. Using 15 authentic medical images at six threshold levels, AO's segmentation performance is compared against eight distinguished algorithms. Experimental results demonstrated AO's superiority in terms of image segmentation accuracy, Feature Similarity Index (FSIM), Peak Signal-to-Noise Ratio (PSNR), and Structural Similarity Index (SSIM) over the contrast algorithms. These results emphasize AO's efficiency and its potential in real-world optimization applications. The source codes

Code snippet in the archive: a link on aliasgharheidari.com (archive link, not checked and not linked: not a code host this site links to).

Papers archive 2025-07-28

30 shown of 66, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

20 shown of 58 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Object Tracking11
Visual Object Tracking10
Visual Tracking7
Video Object Tracking6
GPU4
Object4
ISAC3
Integrated sensing and communication3
Reinforcement Learning (RL)3
Authorship Attribution2
BIG-bench Machine Learning2
Benchmarking2
Classification2
Fairness2
General Classification2
Position2
Text Generation2
reinforcement-learning2
Adversarial Robustness1
Articles1

Usage over time archive 2025-07-28

Papers per year tagged with AO: 2013 to 2025, peak 15 15 0 2013: 1 paper 2013 2014: 1 paper 2014 2015: 2 papers 2015 2016: 0 papers 2016 2017: 0 papers 2017 2018: 0 papers 2018 2019: 7 papers 2019 2020: 5 papers 2020 2021: 5 papers 2021 2022: 7 papers 2022 2023: 15 papers 2023 2024: 14 papers 2024 2025: 9 papers 2025
Papers per year the archive tags with this method, by the paper's archive date (66 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Stochastic Optimization

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