A great number of improved fuzzy c-means (FCM) clustering algorithms have been widely
used for grayscale and color image segmentation. However, most of them are time …

Underwater image quality is seriously degraded due to the insufficient light in water.
Although artificial illumination can assist imaging, it often brings non-uniform illumination …

In order to explore the application value of deep learning denoising autoencoder (DAE) in
Internet-of-Things (IoT) fusion security, in this study, a hierarchical intrusion security …

In order to protect industrial safety, improve the operation stability of the industrial control
system, conduct the response measures for network environment attacked by the external …

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

Interfacial solar steam generation (ISSG) has received increasing attention in both industry
and academia, and is considered a method with great potential for wastewater treatment …

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 …

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 …

Membership regularized fuzzy clustering methods apply an important prior that neighboring
data points should possess similar memberships according to an affinity/similarity matrix. As …

In 2014, a novel clustering algorithm called Density Peak Clustering (DPC) was proposed in
journal Science, which has received great attention in many fields due to its simplicity and …