Добірка наукової літератури з теми "Chlorophyll Content Prediction"
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Статті в журналах з теми "Chlorophyll Content Prediction"
Lv, Jie, Feng Li Deng, and Zhen Guo Yan. "Using PROSEPCT and SVM for the Estimation of Chlorophyll Concentration." Advanced Materials Research 989-994 (July 2014): 2184–87. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.2184.
Повний текст джерелаLiu, Yang, Jinfei Zhao, Yurong Tang, Xin Jiang, and Jiean Liao. "Construction of a Chlorophyll Content Prediction Model for Predicting Chlorophyll Content in the Pericarp of Korla Fragrant Pears during the Storage Period." Agriculture 12, no. 9 (August 31, 2022): 1348. http://dx.doi.org/10.3390/agriculture12091348.
Повний текст джерелаXu, Yanan, Keling Tu, Ying Cheng, Haonan Hou, Hailu Cao, Xuehui Dong, and Qun Sun. "Application of Digital Image Analysis to the Prediction of Chlorophyll Content in Astragalus Seeds." Applied Sciences 11, no. 18 (September 19, 2021): 8744. http://dx.doi.org/10.3390/app11188744.
Повний текст джерелаZhao, Long, Zhao Mei Qiu, Peng Jun Mao, and Gui Yang Deng. "Research on Biological Materials for the Preferred of the Chlorophyll Content Gray GM (1,1) Prediction Models Based on the Different Light." Advanced Materials Research 910 (March 2014): 65–69. http://dx.doi.org/10.4028/www.scientific.net/amr.910.65.
Повний текст джерелаJin, Xiu Liang, Chang Wei Tan, Jun Chan Wang, Lu Tong, Fen Tuan Yang, Xin Kai Zhu, and Wen Shan Guo. "Estimation of Wheat Chlorophyll Content Based on HJ Satellite CCD." Advanced Materials Research 468-471 (February 2012): 1599–604. http://dx.doi.org/10.4028/www.scientific.net/amr.468-471.1599.
Повний текст джерелаAli, Abebe Mohammed, Roshanak Darvishzadeh, Andrew Skidmore, Marco Heurich, Marc Paganini, Uta Heiden, and Sander Mücher. "Evaluating Prediction Models for Mapping Canopy Chlorophyll Content Across Biomes." Remote Sensing 12, no. 11 (June 1, 2020): 1788. http://dx.doi.org/10.3390/rs12111788.
Повний текст джерелаP. SHANMUGAPRIYA, K. R. LATHA, S. PAZHANIVELAN, R. KUMARAPERUMAL, G. KARTHIKEYAN, and N. S. SUDARMANIAN. "Cotton yield prediction using drone derived LAI and chlorophyll content." Journal of Agrometeorology 24, no. 4 (December 2, 2022): 348–52. http://dx.doi.org/10.54386/jam.v24i4.1770.
Повний текст джерелаShafiq Amirul Sabri, Mohd, R. Endut, C. B. M. Rashidi, A. R. Laili, S. A. Aljunid, and N. Ali. "Analysis of Near-infrared (NIR) spectroscopy for chlorophyll prediction in oil palm leaves." Bulletin of Electrical Engineering and Informatics 8, no. 2 (June 1, 2019): 506–13. http://dx.doi.org/10.11591/eei.v8i2.1412.
Повний текст джерелаLarson, James E., Penelope Perkins-Veazie, and Thomas M. Kon. "Apple Fruitlet Abscission Prediction. II. Characteristics of Fruitlets Predicted to Persist or Abscise by Reflectance Spectroscopy Models." HortScience 58, no. 9 (September 2023): 1095–103. http://dx.doi.org/10.21273/hortsci17245-23.
Повний текст джерелаDamayanti, R., D. F. A. Riza, A. W. Putranto, and R. J. Nainggolan. "Vernonia Amygdalina Chlorophyll Content Prediction by Feature Texture Analysis of Leaf Color." IOP Conference Series: Earth and Environmental Science 757, no. 1 (May 1, 2021): 012026. http://dx.doi.org/10.1088/1755-1315/757/1/012026.
Повний текст джерелаДисертації з теми "Chlorophyll Content Prediction"
Paul, Subir. "Hyperspectral Remote Sensing for Land Cover Classification and Chlorophyll Content Estimation using Advanced Machine Learning Techniques." Thesis, 2020. https://etd.iisc.ac.in/handle/2005/4537.
Повний текст джерелаЧастини книг з теми "Chlorophyll Content Prediction"
Kogan, Felix N. "NOAA/AVHRR Satellite Data-Based Indices for Monitoring Agricultural Droughts." In Monitoring and Predicting Agricultural Drought. Oxford University Press, 2005. http://dx.doi.org/10.1093/oso/9780195162349.003.0013.
Повний текст джерелаТези доповідей конференцій з теми "Chlorophyll Content Prediction"
Khoshrou, Mohsen Imanzadeh, Payam Zarafshan, Mohammad Dehghani, Gholamreza Chegini, Akbar Arabhosseini, and Behzad Zakeri. "Deep Learning Prediction of Chlorophyll Content in Tomato Leaves." In 2021 9th RSI International Conference on Robotics and Mechatronics (ICRoM). IEEE, 2021. http://dx.doi.org/10.1109/icrom54204.2021.9663468.
Повний текст джерелаYankun Peng, Hui Huang, Wei Wang, Xiu Wang, Jianhu Wu, and Leilei Zhang. "Prediction of Chlorophyll Content in Wheat Leaves Using Hyperspectral Images." In 2010 Pittsburgh, Pennsylvania, June 20 - June 23, 2010. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2010. http://dx.doi.org/10.13031/2013.29919.
Повний текст джерелаZhang, Ying, Caijuan Li, and Xiaohua Hu. "Content prediction of Chlorophyll-a in seawater based on Fuzzy BP method." In 2011 Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2011). IEEE, 2011. http://dx.doi.org/10.1109/fskd.2011.6019495.
Повний текст джерелаYao Zhang, Lihua Zheng, Minzan Li, Hong Sun, and Qin Zhang. "Prediction of Water Chlorophyll-a Content Based on Multi-scale Spectral Analysis." In 2013 Kansas City, Missouri, July 21 - July 24, 2013. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2013. http://dx.doi.org/10.13031/aim.20131620105.
Повний текст джерелаYankun Peng, Wei Wang, Hui Huang, Xiu Wang, and Xiaodong Gao. "Prediction of Chlorophyll Content of Winter Wheat using Leaf-level Hyperspectral Imaging Data." In 2009 Reno, Nevada, June 21 - June 24, 2009. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2009. http://dx.doi.org/10.13031/2013.27133.
Повний текст джерелаLi, Yunmei. "Applicability of linear regression equation for prediction of chlorophyll content in rice leaves." In Optics & Photonics 2005, edited by Wei Gao and David R. Shaw. SPIE, 2005. http://dx.doi.org/10.1117/12.613208.
Повний текст джерелаSaputro, Adhi Harmoko, Syifa Dzulhijjah Juansyah, and Windri Handayani. "Banana (Musa sp.) maturity prediction system based on chlorophyll content using visible-NIR imaging." In 2018 International Conference on Signals and Systems (ICSigSys). IEEE, 2018. http://dx.doi.org/10.1109/icsigsys.2018.8373569.
Повний текст джерелаWang, Xu, Guoyin Wang, and Xuerui Zhang. "Prediction of Chlorophyll-a content using hybrid model of least squares support vector regression and radial basis function neural networks." In 2016 Sixth International Conference on Information Science and Technology (ICIST). IEEE, 2016. http://dx.doi.org/10.1109/icist.2016.7483440.
Повний текст джерелаDing, Yong-jun, Min-zan Li, Shu-qiang Li, and Deng-kui An. "Predicting chlorophyll content of greenhouse tomato with ground-based remote sensing." In SPIE Asia-Pacific Remote Sensing, edited by Allen M. Larar, Hyo-Sang Chung, and Makoto Suzuki. SPIE, 2010. http://dx.doi.org/10.1117/12.866205.
Повний текст джерелаChen, Yongjie, Lihua Zheng, Minjuan Wang, Mengliu Wu, and Wanlin Gao. "Prediction of chlorophyll and anthocyanin contents in purple lettuce based on image processing." In 2020 ASABE Annual International Virtual Meeting, July 13-15, 2020. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2020. http://dx.doi.org/10.13031/aim.202000544.
Повний текст джерелаЗвіти організацій з теми "Chlorophyll Content Prediction"
Alchanatis, Victor, Stephen W. Searcy, Moshe Meron, W. Lee, G. Y. Li, and A. Ben Porath. Prediction of Nitrogen Stress Using Reflectance Techniques. United States Department of Agriculture, November 2001. http://dx.doi.org/10.32747/2001.7580664.bard.
Повний текст джерелаSeginer, Ido, Daniel H. Willits, Michael Raviv, and Mary M. Peet. Transpirational Cooling of Greenhouse Crops. United States Department of Agriculture, March 2000. http://dx.doi.org/10.32747/2000.7573072.bard.
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