YOLOv8-TF: Transformer-Enhanced YOLOv8 for Underwater Fish Species Recognition with Class Imbalance Handling

YOLOv8-TF: Transformer-Enhanced YOLOv8 for Underwater Fish Species Recognition with Class Imbalance Handling

In video-based fish surveys, species recognition plays a vital role in stock assessments, ecosystem analysis, production management, and protection of endangered species. However, implementing fish species detection algorithms in underwater environments presents significant challenges due to factors...

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Bibliographic Details
Main Authors: Chiranjibi Shah, M M Nabi, Simegnew Yihunie Alaba, Iffat Ara Ebu, Jack Prior, Matthew D. Campbell, Ryan Caillouet, Matthew D. Grossi, Timothy Rowell, Farron Wallace, John E. Ball, Robert Moorhead
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Sensors
Subjects:
fish species recognition
SEAMAPD21
YOLOv8-TF
object detection
Online Access:https://www.mdpi.com/1424-8220/25/6/1846
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