dc.contributor.author |
Wang, CC |
|
dc.contributor.author |
Samani, H |
|
dc.contributor.author |
Yang, CY |
|
dc.contributor.editor |
Sudantha, BH |
|
dc.date.accessioned |
2022-11-18T08:04:14Z |
|
dc.date.available |
2022-11-18T08:04:14Z |
|
dc.date.issued |
2019-12 |
|
dc.identifier.citation |
C. -C. Wang, H. Samani and C. -Y. Yang, "Object Detection with Deep Learning for Underwater Environment," 2019 4th International Conference on Information Technology Research (ICITR), 2019, pp. 1-6, doi: 10.1109/ICITR49409.2019.9407797. |
en_US |
dc.identifier.uri |
http://dl.lib.uom.lk/handle/123/19568 |
|
dc.description.abstract |
In this research we have investigated the usage of deep learning algorithms for object detection in underwater environment and specifically we have employed YOLOv3 algorithm in our study. Details of the algorithm and experimental results are presented. We used available underwater database for training and investigated the method by experimenting to detect and identify the type of the fish in an aquarium in the lab. The results are also explained in this paper. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa, Sri Lanka |
en_US |
dc.relation.uri |
https://ieeexplore.ieee.org/document/9407797 |
en_US |
dc.subject |
Deep Learning |
en_US |
dc.subject |
Object Detection |
en_US |
dc.subject |
YOLO |
en_US |
dc.subject |
Underwater |
en_US |
dc.title |
Object detection with deep learning for underwater environment |
en_US |
dc.type |
Conference-Full-text |
en_US |
dc.identifier.faculty |
IT |
en_US |
dc.identifier.department |
Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa. |
en_US |
dc.identifier.year |
2019 |
en_US |
dc.identifier.conference |
4th International Conference in Information Technology Research 2019 |
en_US |
dc.identifier.place |
Colombo,Sri Lanka |
en_US |
dc.identifier.proceeding |
Proceedings of the 4th International Conference in Information Technology Research 2019 |
en_US |
dc.identifier.doi |
doi: 10.1109/ICITR49409.2019.9407797 |
en_US |