Hierarchical growing cell structures: TreeGCS

VideoGCS - A Clustering-Based System for Video Summarization and Browsing

We present a new approach for MPEG-2 video summarization and browsing based on the Growing Cell Structures (GCS) neural algorithms. Our system VideoGCS first applies GCS to select keyframes for each shot using the color histograms of the dc-images of I frames. These keyframes are then clustered by TreeGCS to form a hierarchical view of the video for efficient browsing. GCS is able to capture ve...

TreeGNG - hierarchical topological clustering

This paper presents TreeGNG, a top-down unsupervised learning method that produces hierarchical classification schemes. TreeGNG extends the Growing Neural Gas algorithm by maintaining a time history of the learned topological mapping. TreeGNG is able to recover from poor decisions made during the construction of the tree, and provides the novel ability to influence the general shape of the hier...

Hierarchical Growing Cell Structures

Hierarchical Growing Cell

We propose a hierarchical self-organizing neural network (\HiGS") with adaptive architecture and simple topological organization. This network combines features of Fritzke's Growing Cell Structures and traditional hierarchical clustering algorithms. The height and width of the tree structure depend on the user-speciied level of error desired, and the weights in upper layers of the network do no...

Uncertainty analysis of hierarchical granular structures for multi-granulation typical hesitant fuzzy approximation space

Hierarchical structures and uncertainty measures are two main aspects in granular computing, approximate reasoning and cognitive process. Typical hesitant fuzzy sets, as a prime extension of fuzzy sets, are more flexible to reflect the hesitance and ambiguity in knowledge representation and decision making. In this paper, we mainly investigate the hierarchical structures and uncertainty measure...