| dc.contributor.author | Weerakone, Shevin | |
| dc.date.accessioned | 2024-05-07T03:58:08Z | |
| dc.date.available | 2024-05-07T03:58:08Z | |
| dc.date.issued | 2023 | |
| dc.identifier.citation | Weerakone, Shevin (2023) Whale and Dolphin Species Detection. BSc. Dissertation, Informatics Institute of Technology | en_US |
| dc.identifier.issn | 2019393 | |
| dc.identifier.uri | http://dlib.iit.ac.lk/xmlui/handle/123456789/2121 | |
| dc.description.abstract | "Whale and dolphin watching is a popular recreational activity in Sri Lanka. However, the approach that is currently in use by the whale and dolphin watching guides is a very primitive one which involves simply using a combination of experience and pure luck. This is highly disadvantageous as it is not a consistent approach by any means and as a result, is certainly far from being the most efficient. There have not been any approaches to develop a system to aid the guides of the whale and dolphin industry in Sri Lanka, in detecting the location of the whales and dolphins accurately. This brings up the problem of a potential wastage of both time as well as fuel and a possible decline of future customers. This work focuses on the development of a system that has the capability to store whale and dolphin images, manage and update them. The design, development and evaluation of the mentioned system are addressed in this document." | en_US |
| dc.language.iso | en | en_US |
| dc.subject | Whale and Dolphin Watching | en_US |
| dc.subject | Image Processing | en_US |
| dc.subject | Angular | en_US |
| dc.title | Whale and Dolphin Species Detection | en_US |
| dc.type | Thesis | en_US |