- Title
- Exploring The Incremental Improvements of YOLOv7 on Bull Sharks in Mozambique
- Creator
- Kuhlane, Luxolo L, Brown, Dane L, Brown, Alden
- Subject
- To be catalogued
- Date
- 2023
- Type
- text
- Type
- article
- Identifier
- http://hdl.handle.net/10962/464118
- Identifier
- vital:76478
- Identifier
- xlink:href="https://www.researchgate.net/profile/Dane-Brown-2/publication/368455814_Exploring_The_Incremental_Improvements_of_YOLOv7_on_Bull_Sharks_in_Mozambique/links/63e8d321dea6121757a4ba7f/Exploring-The-Incremental-Improvements-of-YOLOv7-on-Bull-Sharks-in-Mozambique.pdf?origin=journalDetailand_tp=eyJwYWdlIjoiam91cm5hbERldGFpbCJ9"
- Description
- Scientists use bull shark data to better understand marine organisms and to reduce the likelihood of bull shark extinction. Sharks play an important role in the ocean, and their importance is underappreciated by the general public, leading to negative attitudes toward sharks. The tracking and identification of sharks is done by hand, which is inefficient and time-consuming. This paper employs a deep learning approach to assist in the identification and tracking of bull sharks in Mozambique. YOLO is a popular object detection system used in this paper to aid in the identification of the great white shark. In addition to YOLO, the paper employs ESRGAN to help upscale low-quality images from the datasets into higher-quality images before they are fed into the YOLO system. The primary goal of this paper is to assist in training the system to identify bull sharks in difficult conditions such as murky water or unclear deep-sea conditions.
- Format
- computer, online resource, application/pdf, 1 online resource (15 pages), pdf
- Publisher
- SpringerLink
- Language
- English
- Relation
- Computing and Data Analysis. International Conference Proceedings Series, Kuhlane, L., Brown, D. and Brown, A., 2023. Exploring The Incremental Improvements of YOLOv7 on Bull Sharks in Mozambique. Computing and Data Analysis. International Conference Proceedings Series, Computing and Data Analysis. International Conference Proceedings Series 2023 979-8-4007-0057-6
- Rights
- Publisher
- Rights
- Use of this resource is governed by the terms and conditions of the SpringerLink Terms of Use Statement ( https://link.springer.com/termsandconditions)
- Rights
- Closed Access
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- Visitors: 43
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Collections
Brown, Dane A (Dr)
RU Department of Computer Science
SDG 09. Industry, Innovation and Infrastructure
SDG 14. Life Below Water
| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | SOURCE1 | Exploring The Incremental Improvements of YOLOv7 on Bull Sharks in Mozambique.pdf | 700 KB | Adobe Acrobat PDF | View Details Download |