http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
( Keishiro Kuma ),( Takeshi Yusa ),( Yutaka Kaizu ),( Kenji Imou ) 한국농업기계학회 2018 한국농업기계학회 학술발표논문집 Vol.23 No.1
Degradation of wetlands due to the overgrowth of aquatic plants is a problem in various areas; hence, vegetation management using robot boats is under development. Herein, we proposed a method to recognize aquatic plants via real-time image processing to enable the automation of a robot boat. We adopted a segmentation method using deep learning for image processing and conducted deep learning and testing on our own dataset. An NVIDIA Jetson TX 2 embedded AI computing device achieved an execution time of 1.31 fps (image size: 576 × 324 px). The traveling speed of the robot boat was considerably slow at 0.3 m s<sup>-1</sup>; hence, the boat can be implemented as a real-time system even at a processing speed of 1.31 fps.