Chlorophyll estimation in soybean leaves infield with smartphone digital imaging and machine learning O Hassanijalilian, C Igathinathane, C Doetkott, S Bajwa, J Nowatzki, ... Computers and electronics in agriculture 174, 105433, 2020 | 54 | 2020 |
Estimation of reference evapotranspiration using spatial and temporal machine learning approaches A Rashid Niaghi, O Hassanijalilian, J Shiri Hydrology 8 (1), 25, 2021 | 30 | 2021 |
Rating iron deficiency in soybean using image processing and decision-tree based models O Hassanijalilian, C Igathinathane, S Bajwa, J Nowatzki Remote Sensing 12 (24), 4143, 2020 | 10 | 2020 |
Decoding common machine learning methods: agricultural application case studies using open source software SN Subhashree, S Sunoj, O Hassanijalilian, C Igathinathane Applied Intelligent Decision Making in Machine Learning, 21-52, 2020 | 2 | 2020 |
Soybean leaf chlorophyll estimation and iron deficiency field rating determination at plot and field scales through image processing and machine learning O Hassanijalilian North Dakota State University, 2020 | 1 | 2020 |
Evaluation of Machine Learning Techniques for Daily Reference Evapotranspiration Estimation AR Niaghi, O Hassanijalilian, J Shiri Preprints, 2019 | 1 | 2019 |
Supply Chain Model to Compare the Biorefinery Economics and Environmental Performance of Baled and Pelleted Biomass System R Pandey, O Hassanijalilian, SA Esmaeili, SW Pryor, G Pourhashem BioEnergy Research 17 (1), 334-345, 2024 | | 2024 |
Measuring soybean iron deficiency chlorosis progression and yield prediction with unmanned aerial vehicle O Hassanijalilian, C Igathinathane, S Day, S Bajwa, J Nowatzki Smart Agricultural Technology 4, 100204, 2023 | | 2023 |