| Deepcorn: A semi-supervised deep learning method for high-throughput image-based corn kernel counting and yield estimation S Khaki, H Pham, Y Han, A Kuhl, W Kent, L Wang Knowledge-Based Systems 218, 106874, 2021 | 60 | 2021 |
| Convolutional neural networks for image-based corn kernel detection and counting S Khaki, H Pham, Y Han, A Kuhl, W Kent, L Wang Sensors 20 (9), 2721, 2020 | 51 | 2020 |
| The predicted cross value for genetic introgression of multiple alleles Y Han, JN Cameron, L Wang, WD Beavis Genetics 205 (4), 1409-1423, 2017 | 50 | 2017 |
| An applied deep learning approach for estimating soybean relative maturity from UAV imagery to aid plant breeding decisions S Moeinizade, H Pham, Y Han, A Dobbels, G Hu Machine Learning with Applications 7, 100233, 2022 | 26 | 2022 |
| Systematic design for trait introgression projects JN Cameron, Y Han, L Wang, WD Beavis Theoretical and applied genetics 130, 1993-2004, 2017 | 23 | 2017 |
| High-throughput image-based plant stand count estimation using convolutional neural networks S Khaki, H Pham, Z Khalilzadeh, A Masoud, N Safaei, Y Han, W Kent, ... Plos one 17 (7), e0268762, 2022 | 17 | 2022 |
| A look-ahead Monte Carlo simulation method for improving parental selection in trait introgression S Moeinizade, Y Han, H Pham, G Hu, L Wang Scientific reports 11 (1), 3918, 2021 | 15 | 2021 |
| Dynamic Programming for Resource Allocation in Multi-allelic Trait Introgression Y Han, JN Cameron, L Wang, H Pham, WD Beavis Frontiers in Plant Science 12, 1181, 2021 | 3 | 2021 |
| Operations research applications in multi-allelic trait introgression in plant breeding Y Han Iowa State University, 2017 | 2* | 2017 |
| Not yet submitted for publication John Cameron, Ye Han, Lizhi Wang, Bill Beavis Contributions JC programmed the simulations and wrote the initial drafts YH provided support … J Cameron, Y Han The optimization of introgression projects for plant genetic improvement …, 2017 | | 2017 |
| Not yet submitted for publication Contributions JC defined the challenge, programmed the simulations and wrote initial drafts YH provided support with efficient coding methods J Cameron, Y Han, L Wang, B Beavis The optimization of introgression projects for plant genetic improvement …, 2017 | | 2017 |
William BeavisProfessor Iowa State UniversityVerified email at iastate.edu
