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Featured Story
New AI Method Counts Manatee Clusters in Real Time
The Florida Manatee, considered endangered by the International Union for Conservation of Nature, remains at risk of population decline. A vital conservation effort includes accurately counting manatee groups to observe their habits. With this information, scientists can offer guidance on safety regulations for boaters and divers. However, accurate counts present significant challenges. For instance, manatees frequently graze in herds for up to eight hours daily in shallow waters, which can obstruct researchers’ visibility, especially when viewed from the water's surface. Consequently, smaller manatees may be obscured from view. Additionally, visibility can be hindered by water reflections, in which manatees may appear invisible against surface reflection, or are mistaken for rocks or branches.
Though aerial survey data have been used to count manatees, it’s costly, time-consuming, and affected by observer bias, weather conditions and time of day. Pioneering a low-cost solution, the College of Engineering and Computer Science is harnessing the power of artificial intelligence (AI). Using deep learning-based crowd counting, researchers can automatically count manatee numbers in a specified region by capturing images from CCTV cameras. This innovative study tackles the technical challenges of counting in complex outdoor environments and offers potential strategies to aid endangered species conservation.
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