- Title
- Real-Time Detecting and Tracking of Squids Using YOLOv5
- Creator
- Kuhlane, Luxolo L, Brown, Dane L, Marais, Marc
- Subject
- To be catalogued
- Date
- 2023
- Type
- text
- Type
- article
- Identifier
- http://hdl.handle.net/10962/463467
- Identifier
- vital:76411
- Identifier
- xlink:href="https://ieeexplore.ieee.org/abstract/document/10220521"
- Description
- This paper proposes a real-time system for detecting and tracking squids using the YOLOv5 object detection algorithm. The system utilizes a large dataset of annotated squid images and videos to train a YOLOv5 model optimized for detecting and tracking squids. The model is fine-tuned to minimize false positives and optimize detection accuracy. The system is deployed on a GPU-enabled device for real-time processing of video streams and tracking of detected squids across frames. The accuracy and speed of the system make it a valuable tool for marine scientists, conservationists, and fishermen to better understand the behavior and distribution of these elusive creatures. Future work includes incorporating additional computer vision techniques and sensor data to improve tracking accuracy and robustness.
- Format
- computer, online resource, application/pdf, 1 online resource (4 pages), pdf
- Publisher
- IEEE Xplore
- Language
- English
- Relation
- 2023 International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems (icABCD), Kuhlane, L., Brown, D. and Marais, M., 2023, August. Real-Time Detecting and Tracking of Squids Using YOLOv5. In 2023 International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems (icABCD) (pp. 1-5). IEEE, 2023 International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems (icABCD) p. 1 2023
- Rights
- Publisher
- Rights
- Use of this resource is governed by the terms and conditions of the IEEE Xplore Terms of Use Statement (https://ieeexplore.ieee.org/Xplorehelp/overview-of-ieee-xplore/terms-of-use)
- Rights
- Closed Access
- Hits: 41
- Visitors: 41
- Downloads: 1
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 | SOURCE1 | Real-Time Detecting and Tracking of Squids Using YOLOv5.pdf | 719 KB | Adobe Acrobat PDF | View Details |