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Fishes, Volume 9, Issue 8 (August 2024) – 2 articles

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22 pages, 11091 KiB  
Article
RTL-YOLOv8n: A Lightweight Model for Efficient and Accurate Underwater Target Detection
by Guanbo Feng, Zhixin Xiong, Hongshuai Pang, Yunlei Gao, Zhiqiang Zhang, Jiapeng Yang and Zhihong Ma
Fishes 2024, 9(8), 294; https://doi.org/10.3390/fishes9080294 - 24 Jul 2024
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Abstract
Underwater object detection is essential for the advancement of automated aquaculture operations. Addressing the challenges of low detection accuracy and insufficient generalization capabilities for underwater targets, this paper focuses on the development of a novel detection method tailored to such environments. We introduce [...] Read more.
Underwater object detection is essential for the advancement of automated aquaculture operations. Addressing the challenges of low detection accuracy and insufficient generalization capabilities for underwater targets, this paper focuses on the development of a novel detection method tailored to such environments. We introduce the RTL-YOLOv8n model, specifically designed to enhance the precision and efficiency of detecting objects underwater. This model incorporates advanced feature-extraction mechanisms—RetBlock and triplet attention—that significantly improve its ability to discern fine details amidst complex underwater scenes. Additionally, the model employs a lightweight coupled detection head (LCD-Head), which reduces its computational requirements by 31.6% compared to the conventional YOLOv8n, without sacrificing performance. Enhanced by the Focaler–MPDIoU loss function, RTL-YOLOv8n demonstrates superior capability in detecting challenging targets, showing a 1.5% increase in [email protected] and a 5.2% improvement in precision over previous models. These results not only confirm the effectiveness of RTL-YOLOv8n in complex underwater environments but also highlight its potential applicability in other settings requiring efficient and precise object detection. This research provides valuable insights into the development of aquatic life detection and contributes to the field of smart aquatic monitoring systems. Full article
(This article belongs to the Special Issue Intelligent Recognition Research for Fish Behavior)
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11 pages, 2487 KiB  
Article
Wetted Ramps Selectively Block Upstream Passage of Adult Sea Lampreys
by Uli Reinhardt and Nicholas Corniuk
Fishes 2024, 9(8), 293; https://doi.org/10.3390/fishes9080293 - 23 Jul 2024
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Abstract
Dams fragment stream habitats and fishways around dams typically serve few species that are strong swimmers or jumpers. We tested a prototype wetted ramp designed to allow upstream passage of small-bodied fishes while blocking upstream movement of invasive sea lampreys in the Laurentian [...] Read more.
Dams fragment stream habitats and fishways around dams typically serve few species that are strong swimmers or jumpers. We tested a prototype wetted ramp designed to allow upstream passage of small-bodied fishes while blocking upstream movement of invasive sea lampreys in the Laurentian Great Lakes. We tested short, smooth ramps with 5–10 mm water depth in various combinations of ramp angle, water flow, and swim channel width with the aim to selectively block adult migrating sea lampreys (Petromyzon marinus) while passing sub-adult white suckers (Catostomus commersonii) and creek chubs (Semotilus atromaculatus). Sea lampreys easily passed a 0.75 ramp at a 5° angle, but very few individuals passed a similar ramp at a 10° angle, and none passed a longer ramp at a 5° angle. Limiting the amplitude of tailbeats in a narrow channel did not hamper lampreys or the other species. Greater water flow, and thereby greater immersion depth on the ramp, fostered passage for all species. Smaller-bodied individuals of creek chubs and white suckers performed best on the ramp. We showed that wetted ramps could be incorporated into fishways at low-head dams to aid the passage of smaller-bodied fishes while also blocking the spawning migration of adult sea lampreys. Full article
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