Low-Complexity Scalable Architectures for Parallel Computation of Similarity Measures

Towards Low-Complexity Scalable Shared-Memory Architectures

Evaluation of Similarity Measures for Template Matching

Image matching is a critical process in various photogrammetry, computer vision and remote sensing applications such as image registration, 3D model reconstruction, change detection, image fusion, pattern recognition, autonomous navigation, and digital elevation model (DEM) generation and orientation. The primary goal of the image matching process is to establish the correspondence between two ...

Parallel architectures for fuzzy triadic similarity learning

In a context of document co-clustering, we define a new similarity measure which iteratively computes similarity while combining fuzzy sets in a three-partite graph. The fuzzy triadic similarity (FT-Sim) model can deal with uncertainty offers by the fuzzy sets. Moreover, with the development of the Web and the high availability of storage spaces, more and more documents become accessible. Docum...

Models of Parallel Computation and Parallel Complexity

This thesis reviews selected topics from the theory of parallel computation. The research begins with a survey of the proposed models of parallel computation. It examines the characteristics of each model and it discusses its use either for theoretical studies, or for practical applications. Subsequently, it employs common simulation techniques to evaluate the computational power of these model...

New distance and similarity measures for hesitant fuzzy soft sets

The hesitant fuzzy soft set (HFSS), as a combination of hesitant fuzzy and soft sets, is regarded as a useful tool for dealing with the uncertainty and ambiguity of real-world problems. In HFSSs, each element is defined in terms of several parameters with arbitrary membership degrees. In addition, distance and similarity measures are considered as the important tools in different areas such as ...