Slime Mould Algorithm (SMA) is a new stochastic optimizer proposed based on the oscillation mode of slime mould in nature. SMA has several new features with a unique mathematical model that uses adaptive weights to simulate the process of producing positive and negative feedback of the propagation wave of slime mould based on bio-oscillator to form the optimal path for connecting food with excellent exploratory ability and exploitation propensity.
🔗 The source codes of SMA are publicly available at https://aliasgharheidari.com/SMA.html
Paper | Code | Results | Date | Stars |
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Task | Papers | Share |
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Adversarial Attack | 1 | 5.56% |
Image Quality Assessment | 1 | 5.56% |
No-Reference Image Quality Assessment | 1 | 5.56% |
Computational Efficiency | 1 | 5.56% |
Video Generation | 1 | 5.56% |
Property Prediction | 1 | 5.56% |
Self-Supervised Learning | 1 | 5.56% |
Domain Adaptation | 1 | 5.56% |
Chunking | 1 | 5.56% |
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🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |