최소 단어 이상 선택하여야 합니다.
최대 10 단어까지만 선택 가능합니다.
다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
NTIS 바로가기대한원격탐사학회지 = Korean journal of remote sensing, v.38 no.5 pt.1, 2022년, pp.535 - 543
류재현 (국립농업과학원 기후변화평가과) , 한중곤 (국립농업과학원 기후변화평가과) , 안호용 (국립농업과학원 기후변화평가과) , 나상일 (국립농업과학원 기후변화평가과) , 이병모 (국립농업과학원 기후변화평가과) , 이경도 (국립농업과학원 기후변화평가과)
A drone is used to diagnose crop growth and to provide information through images in the agriculture field. In the case of using high spatial resolution drone images, growth information for each object can be produced. However, accurate object detection is required and adjacent objects should be eff...
Andujar, D., M. Weis, and R. Gerhards, 2012. An ultrasonic system for weed detection in cereal crops, Sensors, 12(12): 17343-17357. https://doi.org/10.3390/s121217343
Dhakal, M., Y. Huang, M.A. Locke, K.N. Reddy, M.T. Moore, L.J. Krutz, D. Gholson, and R. Bajgain, 2022. Assessment of cotton and sorghum stand establishment using UAV-based multispectral and DSLR-based RGB imagery, Agrosystems, Geosciences & Environment, 5(2): e20247. https://doi.org/10.1002/agg2.20247
Go, S.H., D.H. Lee, S.I. Na, and J.H. Park, 2022. Analysis of Growth Characteristics of Kimchi Cabbage Using Drone-Based Cabbage Surface Model Image, Agriculture, 12(2): 216. https://doi.org/10.3390/agriculture12020216
Lee, D.H., H.S. Shin, and J.H. Park, 2020. Developing a p-NDVI map for highland kimchi cabbage using spectral information from UAVs and a field spectral radiometer, Agronomy, 10(11): 1798. https://doi.org/10.3390/agronomy10111798
Li, B., X. Xu, J. Han, L. Zhang, C. Bian, L. Jin, and J. Liu, 2019. The estimation of crop emergence in potatoes by UAV RGB imagery, Plant Methods, 15(1): 1-13. https://doi.org/10.1186/s13007-019-0399-7
Na, S.I., Y.H. Lee, J.H. Ryu, D.H. Lee, H.S. Shin, S.J. Kim, J. Cho, J.H. Park, H.Y. Ahn, K.H. So, and K.D. Lee, 2021. Preparation and Application of Cultivation Management Map Using Drone - Focused on Spring Chinese Cabbage -, Korean Journal of Remote Sensing, 37(3): 637-648 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2021.37.3.22
Park, H.G., J.P. Yun, M.Y. Kim, and S.H. Jeong, 2021. Multichannel Object Detection for Detecting Suspected Trees with Pine Wilt Disease Using Multispectral Drone Imagery, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14: 8350-8358. https://doi.org/10.1109/JSTARS.2021.3102218
Ryu, J.H., H.D. Moon, J. Cho, K.D. Lee, H.Y. Ahn, K.H. So, and S.I. Na, 2021. Response of Structural, Biochemical, and Physiological Vegetation Indices Measured from Field-Spectrometer and MultiSpectral Camera Under Crop Stress Caused by Herbicide, Korean Journal of Remote Sensing, 37(6-1): 1559-1572 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2021.37.6.1.6
Sumesh, K.C., S. Ninsawat, and J. Som-ard, 2021. Integration of RGB-based vegetation index, crop surface model and object-based image analysis approach for sugarcane yield estimation using unmanned aerial vehicle, Computers and Electronics in Agriculture, 180: 105903. https://doi.org/10.1016/j.compag.2020.105903
Torres-Sanchez, J., F. Lopez-Granados, and J.M. Pena, 2015. An automatic object-based method for optimal thresholding in UAV images: Application for vegetation detection in herbaceous crops, Computers and Electronics in Agriculture, 114: 43-52. https://doi.org/10.1016/j.compag.2015.03.019
Varela, S., P.R. Dhodda, W.H. Hsu, P.V. Prasad, Y. Assefa, N.R. Peralta, T. Griffin, A. Sharda, L. Ferguson, and I.A. Ciampitti, 2018. Early-season stand count determination in corn via integration of imagery from unmanned aerial systems (UAS) and supervised learning techniques, Remote Sensing, 10(2): 343. https://doi.org/10.3390/rs10020343
Yarak, K., A. Witayangkurn, K. Kritiyutanont, C. Arunplod, and R. Shibasaki, 2021. Oil Palm Tree Detection and Health Classification on High-Resolution Imagery Using Deep Learning, Agriculture, 11(2):183. https://doi.org/10.3390/agriculture11020183
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