| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0492498 |
| utime |
20240103220353.9 |
| mtime |
20180827235959.9 |
| SCOPUS |
85052215669 |
| DOI |
10.1007/978-3-319-97785-0_3 |
| title
(primary) (eng) |
Rotationally Invariant Bark Recognition |
| specification |
| page_count |
10 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0492497 |
| ISBN |
978-3-319-97784-3 |
| ISSN |
0302-9743 |
| title
|
Structural, Syntactic, and Statistical Pattern Recognition : Joint IAPR International Workshop, S+SSPR 2018 |
| page_num |
22-31 |
| publisher |
| place |
Cham |
| name |
Springer Nature Switzerland AG |
| year |
2018 |
|
| editor |
|
| editor |
|
| editor |
|
| editor |
|
| editor |
|
| editor |
| name1 |
Robles-Kelly |
| name2 |
A. |
|
|
| keyword |
Bark recognition |
| keyword |
Tree taxonomy clasification |
| keyword |
Spiral Markov random field model |
| author
(primary) |
| ARLID |
cav_un_auth*0286710 |
| name1 |
Remeš |
| name2 |
Václav |
| full_dept (cz) |
Rozpoznávání obrazu |
| full_dept (eng) |
Department of Pattern Recognition |
| department (cz) |
RO |
| department (eng) |
RO |
| institution |
UTIA-B |
| full_dept |
Department of Pattern Recognition |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0101093 |
| name1 |
Haindl |
| name2 |
Michal |
| full_dept (cz) |
Rozpoznávání obrazu |
| full_dept |
Department of Pattern Recognition |
| department (cz) |
RO |
| department |
RO |
| institution |
UTIA-B |
| full_dept |
Department of Pattern Recognition |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| abstract
(eng) |
An efficient bark recognition method based on a novel wide-sense Markov spiral model textural representation is presented. Unlike the alternative bark recognition methods based on various gray-scale discriminative textural descriptions, we benefit from fully descriptive color, rotationally invariant bark texture representation. The proposed method significantly outperforms the state-of-the-art bark recognition approaches in terms of the classification accuracy. |
| action |
| ARLID |
cav_un_auth*0363300 |
| name |
IAPR Joint International Workshop on Statistical Techniques in Pattern Recognition and Structural and Syntactic Pattern Recognition |
| dates |
20180817 |
| mrcbC20-s |
20180819 |
| place |
Beijing |
| country |
CN |
|
| RIV |
BD |
| FORD0 |
20000 |
| FORD1 |
20200 |
| FORD2 |
20205 |
| reportyear |
2019 |
| num_of_auth |
2 |
| presentation_type |
PO |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0286554 |
| confidential |
S |
| article_num |
3 |
| mrcbT16-s |
0.339 |
| mrcbT16-4 |
Q2 |
| mrcbT16-E |
Q2 |
| arlyear |
2018 |
| mrcbU14 |
85052215669 SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
WOS |
| mrcbU63 |
cav_un_epca*0492497 Structural, Syntactic, and Statistical Pattern Recognition : Joint IAPR International Workshop, S+SSPR 2018 978-3-319-97784-3 0302-9743 22 31 Cham Springer Nature Switzerland AG 2018 Lecture Notes in Computer Science 11004 |
| mrcbU67 |
340 Bai X. |
| mrcbU67 |
340 Hancock E. |
| mrcbU67 |
340 Ho T. |
| mrcbU67 |
340 Wilson R. |
| mrcbU67 |
340 Biggio B. |
| mrcbU67 |
340 Robles-Kelly A. |
|