| A recommended calibration and validation strategy for hydrologic and water quality models P Daggupati, N Pai, S Ale, KR Douglas-Mankin, RW Zeckoski, J Jeong, ... Transactions of the ASABE 58 (6), 1705-1719, 2015 | 254 | 2015 |
| A survey on using deep learning techniques for plant disease diagnosis and recommendations for development of appropriate tools A Ahmad, D Saraswat, A El Gamal Smart Agricultural Technology 3, 100083, 2023 | 232 | 2023 |
| Performance of deep learning models for classifying and detecting common weeds in corn and soybean production systems A Ahmad, D Saraswat, V Aggarwal, A Etienne, B Hancock Computers and Electronics in Agriculture 184, 106081, 2021 | 154 | 2021 |
| SWAT2009_LUC: A tool to activate the land use change module in SWAT 2009 N Pai, D Saraswat Transactions of the ASABE 54 (5), 1649-1658, 2011 | 104 | 2011 |
| Hydrologic and water quality models: Key calibration and validation topics DN Moriasi, RW Zeckoski, JG Arnold, C Baffaut, RW Malone, P Daggupati, ... Transactions of the ASABE 58 (6), 1609-1618, 2015 | 95 | 2015 |
| A two-stage deep-learning based segmentation model for crop disease quantification based on corn field imagery LG Divyanth, A Ahmad, D Saraswat Smart Agricultural Technology 3, 100108, 2023 | 88 | 2023 |
| Toward generalization of deep learning-based plant disease identification under controlled and field conditions A Ahmad, A El Gamal, D Saraswat IEEE Access 11, 9042-9057, 2023 | 66 | 2023 |
| Smartphone-based hierarchical crowdsourcing for weed identification M Rahman, B Blackwell, N Banerjee, D Saraswat Computers and Electronics in Agriculture 113, 14-23, 2015 | 61 | 2015 |
| Identifying priority subwatersheds in the Illinois River drainage area in Arkansas watershed using a distributed modeling approach N Pai, D Saraswat, M Daniels Transactions of the ASABE 54 (6), 2181-2196, 2011 | 51 | 2011 |
| Deep learning-based object detection system for identifying weeds using uas imagery A Etienne, A Ahmad, V Aggarwal, D Saraswat Remote Sensing 13 (24), 5182, 2021 | 47 | 2021 |
| Flash drought: Review of concept, prediction and the potential for machine learning, deep learning methods S Tyagi, X Zhang, D Saraswat, S Sahany, SK Mishra, D Niyogi Earth's Future 10 (11), e2022EF002723, 2022 | 46 | 2022 |
| Development and evaluation of targeted marginal land mapping approach in SWAT model for simulating water quality impacts of selected second generation biofeedstock G Singh, D Saraswat Environmental modelling & software 81, 26-39, 2016 | 44 | 2016 |
| Field_SWAT: A tool for mapping SWAT output to field boundaries N Pai, D Saraswat, R Srinivasan Computers & Geosciences 40, 175-184, 2012 | 44 | 2012 |
| Machine learning approaches to automate weed detection by UAV based sensors A Etienne, D Saraswat Autonomous air and ground sensing systems for agricultural optimization and …, 2019 | 40 | 2019 |
| CD&S dataset: Handheld imagery dataset acquired under field conditions for corn disease identification and severity estimation A Ahmad, D Saraswat, AE Gamal, G Johal arXiv preprint arXiv:2110.12084, 2021 | 38 | 2021 |
| Biofuels and water quality: challenges and opportunities for simulation modeling B Engel, I Chaubey, M Thomas, D Saraswat, P Murphy, B Bhaduri Biofuels 1 (3), 463-477, 2010 | 37 | 2010 |
| The impact of temperature and shallow hydrologic conditions on the magnitude and spatial pattern consistency of electromagnetic induction measured soil electrical conductivity. BJ Allred, MR Ehsani, D Saraswat | 34 | 2005 |
| Hydrologic and water quality models: Documentation and reporting procedures for calibration, validation, and use D Saraswat, JR Frankenberg, N Pai, S Ale, P Daggupati, ... Transactions of the ASABE 58 (6), 1787-1797, 2015 | 32 | 2015 |
| Comparison of electromagnetic induction, capacitively-coupled resistivity, and galvanic contact resistivity methods for soil electrical conductivity measurement. BJ Allred, MR Ehsani, D Saraswat | 30 | 2006 |
| Identification of foliar disease regions on corn leaves using SLIC segmentation and deep learning under uniform background and field conditions H Phan, A Ahmad, D Saraswat IEEE Access 10, 111985-111995, 2022 | 29 | 2022 |
Naresh PaiScience Fellow, Bayer CropScienceEmail verificata su bayer.com