bibtype |
M -
Monography Chapter
|
ARLID |
0411021 |
utime |
20240103182256.1 |
mtime |
20060210235959.9 |
ISBN |
1-4020-0953-4 |
title
(primary) (eng) |
Model-based pattern recognition |
publisher |
place |
Dordrecht |
name |
Kluwer |
pub_time |
2003 |
|
specification |
|
serial |
title
|
Pattern Recognition and String Matching |
page_num |
201-236 |
editor |
|
editor |
|
|
keyword |
pattern recognition |
keyword |
multi-dimensional models |
author
(primary) |
ARLID |
cav_un_auth*0101093 |
name1 |
Haindl |
name2 |
Michal |
institution |
UTIA-B |
full_dept |
Department of Pattern Recognition |
fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
COSATI |
09K |
cas_special |
project |
project_id |
GA102/00/0030 |
agency |
GA ČR |
ARLID |
cav_un_auth*0004016 |
|
project |
project_id |
GA106/00/1715 |
agency |
GA ČR |
ARLID |
cav_un_auth*0005263 |
|
project |
project_id |
IST-2001-34744 |
agency |
Commission EC |
country |
XE |
ARLID |
cav_un_auth*0200688 |
|
research |
CEZ:AV0Z1075907 |
abstract
(eng) |
Recognition and processing of multi-dimensional data (or set of spatially related objects) is more accurate and efficient if we take into account all interdependencies between single objects. Objects to be processed are often mutually dependent with a dependency degree related to a distance between two objects in their corresponding data space. These relations can be incorporated into a pattern recognition process through appropriate multi-dimensional data model. |
RIV |
BD |
department |
RO |
permalink |
http://hdl.handle.net/11104/0131108 |
ID_orig |
UTIA-B 20030008 |
arlyear |
2003 |
mrcbU10 |
2003 |
mrcbU10 |
Dordrecht Kluwer |
mrcbU12 |
1-4020-0953-4 |
mrcbU63 |
Pattern Recognition and String Matching 201 236 |
mrcbU67 |
Chen D. 340 |
mrcbU67 |
Cheng X. 340 |
|