| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0578865 |
| utime |
20240402214828.8 |
| mtime |
20231201235959.9 |
| title
(primary) (eng) |
Visual Object Recognition - Traditional Methods Along with Deep Learning Approaches |
| specification |
| page_count |
1 s. |
| media_type |
E |
|
| serial |
| ARLID |
cav_un_epca*0578864 |
| ISSN |
14th Conference of Data Analysis Methods for Software Systems (DAMSS23) |
| title
|
14th Conference of Data Analysis Methods for Software Systems (DAMSS23) |
| page_num |
23-23 |
| publisher |
| place |
Vilnius |
| name |
Vilnius University Press |
| year |
2023 |
|
| editor |
| name1 |
Bernatavičienė |
| name2 |
Jolita |
|
|
| keyword |
Visual Object Recognition |
| keyword |
Deep Learning Approaches |
| keyword |
continuous analysis of the visual field |
| author
(primary) |
| ARLID |
cav_un_auth*0101087 |
| name1 |
Flusser |
| name2 |
Jan |
| institution |
UTIA-B |
| full_dept (cz) |
Zpracování obrazové informace |
| full_dept (eng) |
Department of Image Processing |
| department (cz) |
ZOI |
| department (eng) |
ZOI |
| full_dept |
Department of Image Processing |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| project |
| project_id |
GA21-03921S |
| agency |
GA ČR |
| ARLID |
cav_un_auth*0412209 |
|
| abstract
(eng) |
The talk falls into the area of visual Artificial Intelligence (AI), particularly to image recognition by deep networks. In AI applications such as surveillance systems, autonomous robots, unmanned vehicles, drones, etc., cameras and other visual sensors form the “eyes” of the system while image recognition algorithms substitute the visual cortex of the brain. The key requirement is a continuous (possibly real-time) analysis of the visual field and, in that way, preparing the basis for decision and next action planning. The visual analysis may comprise scene segmentation, detection of objects and persons of interest, recognition of their identity and their behaviour, and even prediction of their next actions. |
| action |
| ARLID |
cav_un_auth*0458962 |
| name |
Conference on DATA ANALYSIS METHODS for Software Systems 2023 /14./ |
| dates |
20231130 |
| mrcbC20-s |
20231202 |
| place |
Druskininkai |
| country |
LT |
|
| RIV |
JD |
| FORD0 |
20000 |
| FORD1 |
20200 |
| FORD2 |
20206 |
| reportyear |
2024 |
| num_of_auth |
1 |
| presentation_type |
ZP |
| inst_support |
RVO:67985556 |
| permalink |
https://hdl.handle.net/11104/0347795 |
| confidential |
S |
| arlyear |
2023 |
| mrcbU14 |
SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
WOS |
| mrcbU63 |
cav_un_epca*0578864 14th Conference of Data Analysis Methods for Software Systems (DAMSS23) Vilnius University Press 2023 Vilnius 23 23 Vilnius University Proceedings vol. 39 2669-0233 |
| mrcbU67 |
Bernatavičienė Jolita 340 |
|