Feature selection (FS) is a critical step in hyperspectral image (HSI) classification, essential for reducing data dimensionality while preserving classification accuracy. However, FS for HSIs remains ...

Researchers at Lorestan University have combined ant colony optimization, reinforcement learning, and opposition-based ...

Researchers at Yazd University developed a binary version of the Puma Optimization Algorithm that achieved 91.53 percent ...