| Machine Learning for High-Throughput Stress Phenotyping in Plants A Singh, B Ganapathysubramanian, AK Singh, S Sarkar Trends in Plant Science 21 (2), 110-124, 2016 | 1057 | 2016 |
| Deep Learning for Plant Stress Phenotyping: Trends and Future Perspectives AK Singh, B Ganapathysubramanian, S Sarkar, A Singh Trends in Plant Science, 2018 | 572 | 2018 |
| An explainable deep machine vision framework for plant stress phenotyping S Ghosal, D Blystone, AK Singh, B Ganapathysubramanian, A Singh, ... Proceedings of the National Academy of Sciences, 10.1073/pnas.1716999115, 2018 | 538 | 2018 |
| Plant disease identification using explainable 3D deep learning on hyperspectral images K Nagasubramanian, S Jones, AK Singh, S Sarkar, A Singh, ... Plant Methods 15 (1), 1-10, 2019 | 320 | 2019 |
| NTIRE 2018 Challenge on Spectral Reconstruction from RGB Images A B, O Ben-Shahar, R Timofte, LV Gool, L Zhang, MH Yang, Z Xiong, ... 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition …, 2018 | 248* | 2018 |
| A real-time phenotyping framework using machine learning for plant stress severity rating in soybean HS Naik, J Zhang, A Lofquist, T Assefa, S Sarkar, D Ackerman, A Singh, ... Plant Methods, 2017 | 209 | 2017 |
| Application of molecular markers to wheat breeding in Canada HS Randhawa, M Asif, C Pozniak, JM Clarke, RJ Graf, SL Fox, ... Plant Breeding 132 (5), 458-471, 2013 | 204 | 2013 |
| Hyperspectral band selection using genetic algorithm and support vector machines for early identification of charcoal rot disease in soybean stems K Nagasubramanian, S Jones, S Sarkar, AK Singh, A Singh, ... Plant methods 14 (1), 1-13, 2018 | 177 | 2018 |
| A weakly supervised deep learning framework for sorghum head detection and counting S Ghosal, B Zheng, SC Chapman, AB Potgieter, DR Jordan, X Wang, ... Plant Phenomics 2019, 2019 | 176 | 2019 |
| Crop yield prediction integrating genotype and weather variables using deep learning J Shook, T Gangopadhyay, L Wu, B Ganapathysubramanian, S Sarkar, ... Plos one 16 (6), e0252402, 2021 | 162* | 2021 |
| A deep learning framework to discern and count microscopic nematode eggs A Akintayo, GL Tylka, AK Singh, B Ganapathysubramanian, A Singh, ... Scientific Reports 8 (1), 9145, 2018 | 129* | 2018 |
| Computer vision and machine learning for robust phenotyping in genome-wide studies J Zhang, HS Naik, T Assefa, S Sarkar, RV Reddy, A Singh, ... Scientific reports 7, 44048, 2017 | 127 | 2017 |
| Genome‐wide association and epistasis studies unravel the genetic architecture of sudden death syndrome resistance in soybean J Zhang, A Singh, DS Mueller, AK Singh The Plant Journal 84 (6), 1124-36, 2015 | 119 | 2015 |
| Raffinose Family Oligosaccharides: Friend or Foe for Human and Plant Health? D Elango, K Rajendran, L Van der Laan, S Sebastiar, J Raigne, ... Frontiers in Plant Science 13, Art. 829118, 2022 | 113 | 2022 |
| Computer vision and machine learning enabled soybean root phenotyping pipeline KG Falk, TZ Jubery, SV Mirnezami, KA Parmley, S Sarkar, A Singh, ... Plant methods 16 (1), 1-19, 2020 | 111 | 2020 |
| Chromosomal location of the cadmium uptake gene (Cdu1) in durum wheat RE Knox, CJ Pozniak, FR Clarke, JM Clarke, S Houshmand, AK Singh Genome 52 (9), 741-747, 2009 | 107 | 2009 |
| Genetic architecture of Charcoal Rot (Macrophomina phaseolina) Resistance in Soybean revealed using a diverse panel SM Coser, RV Chowdareddy, J Zhang, DS Mueller, A Mengistu, K Wise, ... Frontiers in Plant Science 8, 1626, 2017 | 106 | 2017 |
| Genetic variability in arbuscular mycorrhizal fungi compatibility supports the selection of durum wheat genotypes for enhancing soil ecological services and cropping systems in … AK Singh, C Hamel, RM DePauw, RE Knox Canadian journal of microbiology 58 (3), 293-302, 2012 | 106 | 2012 |
| UAS-Based Plant Phenotyping for Research and Breeding Applications W Guo, ME Carroll, A Singh, TL Swetnam, N Merchant, S Sarkar, ... Plant Phenomics 2021, Article ID 9840192, 2021 | 100 | 2021 |
| Machine Learning Approach for Prescriptive Plant Breeding KA Parmley, RH Higgins, B Ganapathysubramanian, S Sarkar, AK Singh Scientific reports 9 (1), 1-12, 2019 | 100 | 2019 |
