Combining Thermal and RGB Imaging Indices with Multivariate and Data-Driven Modeling to Estimate the Growth, Water Status, and Yield of Potato under Different Drip Irrigation Regimes. - Salah Elsayed; Salah El-Hendawy; Mosaad Khadr; Osama Elsherbiny; Nasser Al-Suhaibani; Majed Alotaibi; Muhammad Usman Tahir; Waleed Darwish (Remote. Sens., 2021)

Integration of Visible and Thermal Imagery with an Artificial Neural Network Approach for Robust Forecasting of Canopy Water Content in Rice. - Osama Elsherbiny; Lei Zhou 013; Lei Feng; Zhengjun Qiu (Remote. Sens., 2021)

A novel hybrid deep network for diagnosing water status in wheat crop using IoT-based multimodal data. - Osama Elsherbiny; Lei Zhou 013; Yong He 001; Zhengjun Qiu (Comput. Electron. Agric., 2022)

Developing an IoT-driven delta robot to stimulate the growth of mulberry branch cuttings cultivated aeroponically using machine vision technology. - Osama Elsherbiny; Jianmin Gao; Ming Ma; Waqar Ahmed Qureshi; Abdallah H. Mosha (Comput. Electron. Agric., 2025)

Precision farming: Using an IoT multimodal data-driven deep network to optimize irrigation in wheat crops. - Osama Elsherbiny; Lei Zhou 013; Yong He 001; Zhengjun Qiu (Expert Syst. Appl., 2025)