On Data-Independent Properties for Density-Based Dissimilarity Measures in Hybrid Clustering

Chapter 7: Study case – DNA classification: We presents the problem of DNA classification using Artificial Neural Network and Support Vector Machine, and apply Particle Swarm

This paper proposes a deterministic density clustering algorithm based on DBSCAN that allows to discover arbitrary shaped clusters of spatio-temporal events that (1)

- We propose a hybrid energy function which measures the quality of a orthogonal coordinate frame for 3D objects by considering symmetric properties and rectilinearity.. - We present

To enable similarity based retrieval of neuronal objects we defined together with domain experts tailored dissimilarity measures for each of the three typical neuronal sub

GMap combines graph layout and graph clustering, together with appropriate color- ing of the clusters and creating boundaries based on clus- ters and connectivity in the original

Figure 1: From left to right: Input image, k-means clustering result, result from our clustering-based regularizer and our clustering-based regularizer incorporated in a

In this paper we propose Tonal Art Maps with Image Space Strokes (TAMISS), a hybrid technique that combines the robust visibility testing and density control of TAM or RPTAM with

Therefore, we propose Latent Accessibility Clusters (LACs) by applying graph- based spatial clustering on urban POIs based on their accessibility similarities.. The clusters