|
|
|
|
CONTRIBUTORS:
|
|
|
CONFERENCE NAME:
|
|
|
CONF. LOCATION:
|
Whistler, BC, Canada
|
|
CONFERENCE YEAR:
|
2003
|
|
PUB TYPE:
|
Conference Presentation
|
|
SUBJECT(S):
|
task-oriented image interpretation and object recognition, automated construction of vision systems, reinforcement learning for vision control
|
|
DISCIPLINE:
|
Computer Science
|
|
HTTP:
|
|
|
LANGUAGE:
|
English
|
|
PUB ID:
|
103-397-079
(Last edited on
2003/11/21 20:57:30 US/Mountain)
|
|
SPONSOR(S):
|
|
|
ABSTRACT:
Automated image interpretation and object recognition is an important task in numerous applications ranging from security systems to natural resource inventorization based on remotesensing. Recently, a second generation of adaptive
machine-learned image interpretation systems have shown promising performance in several challenging domains. While demonstrating an unprecedented improvement over handengineered or first generation machine learned systems in terms of cross-domain portability, design cycle time, and robustness, such systems are still severely limited. In this paper we pose several open challenges critical to further progress in learning vision systems. The issues are illustrated with recent efforts and examples.
|
|
|
|
STATISTICS
|
|
Click on # to view
|
|
Citations
|
|
0
|
|
References
|
|
0
|
|
Comments
|
|
0
|
|
Quality
|
|
0/0.00
|
|
Interest
|
|
0/0.00
|
|
View(er)s
|
|
3/217
|
|
|
|
|
|
|
| Prev |
Next |
|
