Data mining is an analytical approach that contributes to achieving a solution to many
problems by extracting previously unknown, fascinating, nontrivial, and potentially valuable …

Underwater image enhancement aims at improving the visibility and eliminating color
distortions of underwater images degraded by light absorption and scattering in water …

Single underwater image enhancement remains a challenging ill-posed problem, even with
advanced deep learning methods, due to the significant information degeneration and …

Light traveling through water results in strong scattering across color channels, restricting
visibility in underwater images. Many cutting-edge underwater image enhancement …

This paper develops a Bayesian retinex algorithm for enhancing single underwater image
with multiorder gradient priors of reflectance and illumination. First, a simple yet effective …

Most of the approaches used for Landslide inventory map** (LIM) rely on traditional
feature extraction and unsupervised classification algorithms. However, it is difficult to use …

Fuzzy C-means (FCM) is a clustering algorithm based on partition of the universe. However,
the partition generated by an equivalence relation is strict in practical application and …

Early identification of melanocytic skin lesions increases the survival rate for skin cancer
patients. Automated melanocytic skin lesion extraction from dermoscopic images using the …

Clustering is one of the most vital image segmentation techniques. However, proper image
clustering has always been a challenging task due to blurred and vague areas near to …

Clustering algorithms by minimizing an objective function share a clear drawback of having
to set the number of clusters manually. Although density peak clustering is able to find the …