Abstract Machine vision significantly improves the efficiency, quality, and reliability of defect
detection. In visual inspection, excellent optical illumination platforms and suitable image …

Gene expression data hide vital information required to understand the biological process
that takes place in a particular organism in relation to its environment. Deciphering the …

We present CLUSTSEG, a general, transformer-based framework that tackles different
image segmentation tasks (ie, superpixel, semantic, instance, and panoptic) through a …

Image segmentation is the classification of an image into different groups. Many researches
have been done in the area of image segmentation using clustering. There are different …

Mixed data comprises both numeric and categorical features, and mixed datasets occur
frequently in many domains, such as health, finance, and marketing. Clustering is often …

The monograph Data Clustering: Theory, Algorithms, and Applications was published in
2007. Starting with the common ground and knowledge for data clustering, the monograph …

Longitudinal studies are essential tools in medical research. In these studies, variables are
not restricted to single measurements but can be seen as variable-trajectories, either single …

This paper proposes a new algorithm for K-medoids clustering which runs like the K-means
algorithm and tests several methods for selecting initial medoids. The proposed algorithm …

Use of traditional k-mean type algorithm is limited to numeric data. This paper presents a
clustering algorithm based on k-mean paradigm that works well for data with mixed numeric …

Clustering is a popular data analysis and data mining problem. Symmetry can be
considered as a pre-attentive feature, which can improve shapes and objects, as well as …