Original title: Nature Inspired Evolutionary Swarm Optimizers for Biomedical Image and Signal Processing — A Systematic Review
Authors: Subhrangshu Adhikary
In the quest for optimal solutions with limited resources, researchers have crafted nature-inspired meta-heuristic optimization algorithms. These draw from natural phenomena and organism behaviors, offering quicker, highly accurate problem-solving abilities. Yet, while these algorithms hold promise for diverse applications—like signal denoising and neural network weight adjustments—there’s a dearth of systematic reviews in biomedical signal processing. Bridging this gap, a comprehensive article examines 28 recent peer-reviewed works. It delves into 26 nature-inspired algorithms, classifying them by their exploration stages—thoroughly explored, less explored, and unexplored. By spotlighting their reliability and exploration levels, this article aids readers in grasping the potential of each algorithm. Additionally, it provides an updated survey of these algorithms’ roles in biomedical image processing. In essence, it offers a roadmap for leveraging these innovative algorithms in biomedical contexts.
Original article: https://arxiv.org/abs/2311.12830