Title
Beyond Simple and Complex Neurons: Towards Intermediate-level Representations of Shapes and Objects.
Abstract
Knowledge of the brain has much advanced since the concept of the neuron doctrine developed by Ramón y Cajal (R Trim Histol Norm Patol 1:33–49, 1888). Over the last six decades a wide range of functionalities of neurons in the visual cortex have been identified. These neurons can be hierarchically organized into areas since neurons cluster according to structural properties and related function. The neurons in such areas can be characterized to a first order approximation by their (static) receptive field function, viz their filter characteristic implemented by their connection weights to neighboring cells. This paper aims to provide insights on the steps that computer models in our opinion must pursue in order to develop robust recognition mechanisms that mimic biological processing capabilities beyond the level of cells with classical simple and complex receptive field response properties. We stress the importance of intermediate-level representations to achieve higher-level object abstraction in the context of feature representations, and summarize two current approaches that we consider are advances toward achieving that goal.
Year
DOI
Venue
2015
10.1007/s13218-014-0341-0
KI
Keywords
Field
DocType
Computer modeling, Intermediate visual processing, Boundary grouping, Shape representation, Feedback connections, junctions
Receptive field,Trim,Visual cortex,Computer science,Abstraction (linguistics),Neuron doctrine,Artificial intelligence,Orders of approximation,Machine learning
Journal
Volume
Issue
ISSN
29
1
1610-1987
Citations 
PageRank 
References 
0
0.34
17
Authors
3
Name
Order
Citations
PageRank
Antonio Jose Rodríguez-Sánchez113416.30
Heiko Neumann264493.84
Justus H. Piater354361.56