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In this paper, we propose a jellyfish distribution management system using an UAV (unmanned aerial vehicle) and USVs (unmanned surface vehicle). The UAV was designed to satisfy the requirements for flight in ocean environment. The target jellyfish, aurelia aurita, is recognized through a convolution neural network and its distribution is calculated. A high-speed deep neural network architecture has...
Jellyfish blooms have caused great damage to the fishery industry. In efforts to solve this problem, various systems to remove jellyfish have been proposed. This letter presents preliminary results of applying an image-based jellyfish distribution recognition algorithm to increase the efficiency of an existing jellyfish removal system. By using a convolutional neural network and dedicated image processing...
In this paper, a novel robot system for a jellyfish reconnaissance and removal using unmanned aerial vehicle (UAV) and unmanned surface vehicle (USV) is introduced. In recent years, overpopulated jellyfish are threatening ocean ecosystem as well as damaging to ocean-related industries such as fishery, seaside power plants, and casualties. The damage is estimated about 300M USD per year in South Korea...
This paper proposes a novel vision-based jellyfish detection algorithm in underwater environment. Since jellyfish, especially Aurelia aurita, is translucent and amorphous when projected to the 2-dimensional image, its boundary is indistinct and detecting jellyfish is very challenging. To detect moving jellyfish, two types of features that present the translucent appearance and swimming motion of jellyfish,...
At present, unmanned aerial vehicles (UAVs) are the primary platforms widely used for environmental monitoring. The advantage of the UAV-type surveillance system is its low-cost with high observation performance. Using this system, we can extend the workable area of the jellyfish removal system. The proposed system observes jellyfish on the surface of the sea while flying, and can recognize a herd...
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