0000000000850833
AUTHOR
Luciano Da Fontoura Costa
Texture Discrimination Using Hierarchical Complex Networks
Texture analysis represents one of the main areas in image processing and computer vision. The current article describes how complex networks have been used in order to represent and characterized textures. More speci?cally, networks are derived from the texture images by expressing pixels as network nodes and similarities between pixels as network edges. Then, measurements such as the node degree, strengths and clustering coe?cient are used in order to quantify properties of the connectivity and topology of the analyzed networks. Because such properties are directly related to the structure of the respective texture images, they can be used as features for characterizing and classifying te…
Panel Summary: Symbolism and Connectionism Paradigms
The aim of this chapter is to report the panel discussion on symbolism and connectionism paradigms. In particular, the following hot point are analysed: what cognitive phenomena are most difficult for connectionists to explain? what cognitive phenomena are most naturally explained in connectionist terms? is symbolic deduction a central kind of human thinking? How do people make deductions? is nondeductive reasoning done in accord with the laws of probability? what areas of knowledge do you have that are easily described in terms of symbolic rules? concepts reduced to rules, concepts reduced to networks; symbolic and connectionist mechanisms of analogy; planning, decision, explanation, learn…