The impact of the number of training samples and the number of test points on the accuracy of land use and land cover maps derived from satellite imagery using machine learning-based classification algorithms: A case study on Al-Ahsa Oasis in Saudi Arabia
Faqeih, K. (2645). The impact of the number of training samples and the number of test points on the accuracy of land use and land cover maps derived from satellite imagery using machine learning-based classification algorithms: A case study on Al-Ahsa Oasis in Saudi Arabia. EKB Journal Management System, 2024(10), -. doi: 10.70216/2682-485X.1671
Khadeijah yahya Faqeih. "The impact of the number of training samples and the number of test points on the accuracy of land use and land cover maps derived from satellite imagery using machine learning-based classification algorithms: A case study on Al-Ahsa Oasis in Saudi Arabia". EKB Journal Management System, 2024, 10, 2645, -. doi: 10.70216/2682-485X.1671
Faqeih, K. (2645). 'The impact of the number of training samples and the number of test points on the accuracy of land use and land cover maps derived from satellite imagery using machine learning-based classification algorithms: A case study on Al-Ahsa Oasis in Saudi Arabia', EKB Journal Management System, 2024(10), pp. -. doi: 10.70216/2682-485X.1671
Faqeih, K. The impact of the number of training samples and the number of test points on the accuracy of land use and land cover maps derived from satellite imagery using machine learning-based classification algorithms: A case study on Al-Ahsa Oasis in Saudi Arabia. EKB Journal Management System, 2645; 2024(10): -. doi: 10.70216/2682-485X.1671