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무인기 기반 RGB 영상 활용 U-Net을 이용한 수수 재배지 분할
박기수,유찬석,강예성,김은리,정종찬,박진기,Kisu Park,Chanseok Ryu,Yeseong Kang,Eunri Kim,Jongchan Jeong,Jinki Park 대한원격탐사학회 2023 大韓遠隔探査學會誌 Vol.39 No.5
When converting rice fields into fields,sorghum (sorghum bicolor L. Moench) has excellent moisture resistance, enabling stable production along with soybeans. Therefore, it is a crop that is expected to improve the self-sufficiency rate of domestic food crops and solve the rice supply-demand imbalance problem. However, there is a lack of fundamental statistics,such as cultivation fields required for estimating yields, due to the traditional survey method, which takes a long time even with a large manpower. In this study, U-Net was applied to RGB images based on unmanned aerial vehicle to confirm the possibility of non-destructive segmentation of sorghum cultivation fields. RGB images were acquired on July 28, August 13, and August 25, 2022. On each image acquisition date, datasets were divided into 6,000 training datasets and 1,000 validation datasets with a size of 512 × 512 images. Classification models were developed based on three classes consisting of Sorghum fields(sorghum), rice and soybean fields(others), and non-agricultural fields(background), and two classes consisting of sorghum and non-sorghum (others+background). The classification accuracy of sorghum cultivation fields was higher than 0.91 in the three class-based models at all acquisition dates, but learning confusion occurred in the other classes in the August dataset. In contrast, the two-class-based model showed an accuracy of 0.95 or better in all classes, with stable learning on the August dataset. As a result, two class-based models in August will be advantageous for calculating the cultivation fields of sorghum.
자연환기량과 포그분무량 조절에 의한 온실 온습도의 동시제어 기법 연구
김영복(Kim Youngbok),성현수(Sung Hyunsoo),황승재(Hwang Seungjae),김현태(Kim Hyeontae),유찬석(Ryu Chanseok) 한국태양에너지학회 2016 한국태양에너지학회 논문집 Vol.36 No.5
To develope a greenhouse fog cooling system to control the temperature and relative humidity simultaneously to the target value, a theoretical analysis and experiments were done. The control process includes the measuring of environmental variables, setting and coding of the water and heat balance equations to maintain the target temperature and relative humidity in greenhouse, calculating of the open level of the greenhouse roof window that governs the natural ventilation and spray water quantity, and operating of the motor to open/close the roof window and pump to spray for water. The study results were shown to be very good because the average air temperature in the greenhouse was kept to be about 28.2℃ with the standard deviation of about 0.37℃ compared to the target temperature of 28℃ and the average relative humidity was about 75.2% compared to the target relative humidity was 75% during the experiments. The average outside relative humidity was about 41.0% and the average outside temperature was 27.2℃ with the standard deviation of about 0.54℃. The average solar intensity in the greenhouse was 712.9 W. The wind velocity of outside greenhouse was 0.558 ㎧ with the standard deviation of 0.46 ㎧.