---
abstract: 'Given the importance of using resources efficiently in the competition for survival, it is reasonable to think that natural evolution has discovered efficient cortical coding strategies for representing natural visual information. Sparse representations have intrinsic advantages in terms of fault-tolerance and low-power consumption potential, and can therefore be attractive for robot sensorimotor control with powerful dispositions for decision-making. Inspired by the mammalian brain and its visual ventral pathway, we present in this paper a hierarchical sparse coding network architecture that extracts visual features for use in sensorimotor control. Testing with natural images demonstrates that this sparse coding facilitates processing and learning in subsequent layers. Previous studies have shown how the responses of complex cells could be sparsely represented by a higher-order neural layer. Here we extend sparse coding in each network layer, showing that detailed modeling of earlier stages in the visual pathway enhances the characteristics of the receptive fields developed in subsequent stages. The yield network is more dynamic with richer and more biologically plausible input and output representation.'
altloc:
- http://www.lucs.lu.se/ftp/pub/LUCS_Studies/LUCS101/Yang.pdf
chapter: ~
commentary: ~
commref: ~
confdates: 'August 4-5, 2003'
conference: 'Third International Workshop on Epigenetic Robotics: Modeling Cognitive Development in Robotic Systems'
confloc: 'Boston, MA, USA'
contact_email: ~
creators_id: []
creators_name:
- family: Yang
given: Li
honourific: ''
lineage: ''
- family: Jabri
given: Marwan
honourific: ''
lineage: ''
date: 2003
date_type: published
datestamp: 2004-02-12
department: ~
dir: disk0/00/00/33/40
edit_lock_since: ~
edit_lock_until: ~
edit_lock_user: ~
editors_id: []
editors_name:
- family: Prince
given: Christopher G.
honourific: ''
lineage: ''
- family: Berthouze
given: Luc
honourific: ''
lineage: ''
- family: Kozima
given: Hideki
honourific: ''
lineage: ''
- family: Bullock
given: Daniel
honourific: ''
lineage: ''
- family: Stojanov
given: Georgi
honourific: ''
lineage: ''
- family: Balkenius
given: Christian
honourific: ''
lineage: ''
eprint_status: archive
eprintid: 3340
fileinfo: /style/images/fileicons/application_pdf.png;/3340/1/Yang.pdf
full_text_status: public
importid: ~
institution: ~
isbn: ~
ispublished: pub
issn: ~
item_issues_comment: []
item_issues_count: 0
item_issues_description: []
item_issues_id: []
item_issues_reported_by: []
item_issues_resolved_by: []
item_issues_status: []
item_issues_timestamp: []
item_issues_type: []
keywords: 'hierarchical sparse coding network, visual ventral pathway, sensorimotor control'
lastmod: 2011-03-11 08:55:25
latitude: ~
longitude: ~
metadata_visibility: show
note: ~
number: ~
pagerange: 131-138
pubdom: TRUE
publication: ~
publisher: Lund University Cognitive Studies
refereed: TRUE
referencetext: ~
relation_type: []
relation_uri: []
reportno: ~
rev_number: 12
series: ~
source: ~
status_changed: 2007-09-12 16:50:12
subjects:
- comp-sci-mach-vis
- comp-sci-neural-nets
- comp-sci-robot
succeeds: ~
suggestions: ~
sword_depositor: ~
sword_slug: ~
thesistype: ~
title: Sparse visual models for biologically inspired sensorimotor control
type: confpaper
userid: 3507
volume: 101