In recent years, bioanalytical surface-enhanced Raman spectroscopy (SERS) has
blossomed into a fast-growing research area. Owing to its high sensitivity and outstanding …

Intuitionistic fuzzy set (IFS) theory is widely used to solve imprecise and uncertain problems,
and the similarity measure between IFSs can describe the similarity or dissimilarity degree of …

The fuzzy local information C-means clustering algorithm (FLICM) is an important robust
fuzzy clustering segmentation method, which has attracted considerable attention over the …

Aiming at existing symmetric regularized picture fuzzy clustering with weak robustness, and
it is difficult to meet the need for image segmentation in the presence of high noise. Hence, a …

Fuzzy clustering algorithm (FCM) can be directly used to segment images, it takes no
account of the neighborhood information of the current pixel and does not have a robust …

Spectral clustering algorithm (SC) has recently received great attention for its high
performance in large-scale data clustering and simplicity in implementation. However …

When the level set algorithm is used to segment an image, the level set function must be
initialized periodically to ensure that it remains a signed distance function (SDF). To avoid …

For spectral clustering algorithm, the quality of eigenvectors of graph affinity matrix is very
important for the clustering result. So, how to obtain high‐quality eigenvectors is crucial. In …

Geometric ability includes elements of identification, conceptualization, combination,
drawing, and reasoning, and graphic perception is an important part of it. Kindergarten …

With the development of autonomous driving, future traffic will be composed of various
participants. Integrating autonomous vehicles into the traffic flow composed of various types …