Abstract Background Medical Image segmentation is an important image processing step.
Comparing images to evaluate the quality of segmentation is an essential part of measuring …

Clustering is a solution for classifying enormous data when there is not any early knowledge
about classes. With emerging new concepts like cloud computing and big data and their vast …

The critical functions of the human liver are coordinated through the interactions of hepatic
parenchymal and non‐parenchymal cells. Recent advances in single‐cell transcriptional …

The network architecture of the human brain has become a feature of increasing interest to
the neuroscientific community, largely because of its potential to illuminate human cognition …

Across many scientific domains, there is a common need to automatically extract a simplified
view or coarse-graining of how a complex system's components interact. This general task is …

Current compression schemes for floating-point data commonly take fixed-precision values
and compress them to a variable-length bit stream, complicating memory management and …

Most clustering strategies have not changed considerably since their initial definition. The
common improvements are either related to the distance measure used to assess …

The validation of the results obtained by clustering algorithms is a fundamental part of the
clustering process. The most used approaches for cluster validation are based on internal …

In agriculture sector where farmers and agribusinesses have to make innumerable
decisions every day and intricate complexities involves the various factors influencing them …

Information theoretic based measures form a fundamental class of similarity measures for
comparing clusterings, beside the class of pair-counting based and set-matching based …