Adaptive Image Interpretation : A Spectrum of Machine Learning Problems
|
 |
|
Post a Comment
|
|
|
|
|
CONTRIBUTORS:
|
|
|
CONFERENCE TITLE:
|
|
|
CONF. LOCATION:
|
None
|
|
YEAR:
|
2003
|
|
PUB TYPE:
|
Conference Paper
|
|
SUBJECT(S):
|
learning from labeled and unlabeled data, automated operator and feature set selection, reinforcement learning, Markov decision processes, adaptive image interpretation.
|
|
DISCIPLINE:
|
Computer Science
|
|
HTTP:
|
|
|
LANGUAGE:
|
English
|
|
PUB ID:
|
103-397-073
(Last edited on
2003/11/21 20:58:44 US/Mountain)
|
|
SPONSOR(S):
|
|
|
ABSTRACT:
Automated image interpretation is an important task in numerous applications ranging from security systems to natural resource inventorization based on remote-sensing. Recently, a second generation of adaptive machine-learned image interpretation systems have shown expertlevel
performance in several challenging domains. While demonstrating an unprecedented improvement over hand-engineered 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 inspect the anatomy of a state-of-the-art adaptive image interpretation system and discuss the range of the corresponding machine learning problems. We then report on the novel machine learning approaches engaged
and the resulting improvements.
|
|
|
|
STATISTICS
|
|
Click on # to view
|
|
Citations
|
|
0
|
|
References
|
|
0
|
|
Comments
|
|
0
|
|
Quality
|
|
0/0.00
|
|
Interest
|
|
0/0.00
|
|
View(er)s
|
|
3/281
|
|
|
|
|
|
|
| Prev |
Next |
|