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Normalization in Proportional Feature Spaces
The subject of features normalization plays an important central role in data representation, characterization, visualization, analysis, comparison, classification, and modeling, as it can substantially influence and be influenced by all of these activities and respective aspects.
Supervised Pattern Recognition Involving Skewed Feature Densities
Several interesting results are described and discussed, including the enhanced potential of the dissimilarity index for classifying datasets with right skewed feature densities, as well as the identification that the sharpness of the comparison between data elements can be independent of the respective supervised classification performance.
Multilayer Multiset Neuronal Networks -- MMNNs
These features allow multiset neurons, which are based on the coincidence similarity operation, to perform effective pattern recognition applications, including the challenging task of image segmentation.
Two Approaches to Supervised Image Segmentation
While the deep learning approach confirmed its potential for performing image segmentation, the alternative multiset methodology allowed for enhanced accuracy while requiring little computational resources.
Neuromorphic Networks as Revealed by Features Similarity
Well-separated groups were obtained that provide a rich representation of the main similarity interrelationships between the 735 considered neuronal cells.
Transistors: A Network Science-Based Historical Perspective
The development of modern electronics was to a large extent related to the advent and popularization of bipolar junction technology.
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