Abstract: Machine learning algorithm for multi-modal image segmentation is extensively employed in medical analysis and diagnosis. Clustering represents a mainstream approach for image segmentation, ...

Metaheuristic algorithms have emerged as powerful tools for partitioning images into meaningful regions by optimising objective functions that characterise homogeneity, boundary conformity and feature ...

If it feels like social platforms suddenly “get” you more than they used to, you’re not imagining it! In 2026, feeds aren’t only reacting to what you click anymore. They’re predicting what you ...

This study aims to investigate the application of visual information processing mechanisms in the segmentation of stem cell (SC) images. The cognitive principles underlying visual information ...

Automated apple harvesting is hindered by clustered fruits, varying illumination, and inconsistent depth perception in complex orchard environments. While deep learning models such as Faster R-CNN and ...

The remarkable performance of large multimodal models (LMMs) has attracted significant interest from the image segmentation community. To align with the next-token-prediction paradigm, current ...

Abstract: There are many algorithms for image segmentation, but there is no optimal algorithm for all kind of image applications. To recommend an adequate algorithm for segmentation is a challenging ...