Multi-level threshold segmentation techniques are one of the most important parts in image processing. They are simple, robust, and accurate. However, some of them have long computation time and it ...

Adaptive Image Preprocessing Pipeline for IOPA X-rays Project Overview This project develops an adaptive preprocessing pipeline for Intraoral Periapical (IOPA) X-ray images, aimed at enhancing image ...

To date, no ecological variable has been identified to explain clownfish niche partitioning, phenotypic evolution, species co-occurrence, and thus, the adaptive aspect of the group’s radiation. Our ...

A new AI algorithm inspired by the genome’s ability to compress vast information offers insights into brain function and potential tech applications.

Attention-based models are proliferating in the space of image analytics, including segmentation. The standard method of feeding images to transformer encoders is to divide the images into patches and ...

To this end, this study proposes an integrated automatic recognition method combining Image Clipping (IC), Image Information Enhancement (IE), Adaptive K-means Clustering Segmentation (AKS), and ...

In order to make full use of the color information of the image and improve the accuracy of color image segmentation, this paper proposes an adaptive SLIC-based fuzzy intensity dissimilarity ...

With the development and wider application of meta-heuristic optimization algorithms, researchers increasingly apply them to threshold optimization of multi-level image segmentation. This paper ...

In this paper, a new intelligence algorithm, particle swarm opti-mization (PSO), is presented for multilevel thresholding in image segmentation. This algorithm is used to maximize the Kapur’s and Otsu ...