no code implementations • 4 May 2021 • Amit Kumar Srivastava, Nima Safaei, Saeed Khaki, Gina Lopez, Wenzhi Zeng, Frank Ewert, Thomas Gaiser, Jaber Rahimi
We used eight supervised machine learning models as baselines and evaluated their predictive performance using RMSE, MAE, and correlation coefficient metrics to benchmark the yield prediction results.
no code implementations • 17 Mar 2021 • Saeed Khaki, Nima Safaei, Hieu Pham, Lizhi Wang
To help mitigate this data collection bottleneck in wheat breeding, we propose a novel deep learning framework to accurately and efficiently count wheat heads to aid in the gathering of real-time data for decision making.
no code implementations • 2 Dec 2020 • Nima Safaei, Pooria Assadi
Regularization is a well-established technique in machine learning (ML) to achieve an optimal bias-variance trade-off which in turn reduces model complexity and enhances explainability.
no code implementations • 4 Dec 2019 • Nima Safaei, Ivan A. Sergienko
We employ the mathematical programming approach in conjunction with the graph theory to study the structure of correspondent banking networks.
no code implementations • 3 Mar 2018 • Nima Safaei, Corey Kiassat
The considered problem is how to optimally allocate a set of jobs to technicians of different skills such that the number of technicians of each skill does not exceed the number of persons with that skill designation.