Order Article Reprints

Kross A, Znoj E, Callegari D, Kaur G, Sunohara M, Lapen DR, McNairn H. Using Artificial Neural Networks and Remotely Sensed Data to Evaluate the Relative Importance of Variables for Prediction of Within-Field Corn and Soybean Yields. Remote Sensing. 2020; 12(14):2230. https://doi.org/10.3390/rs12142230

Kross, Angela, Evelyn Znoj, Daihany Callegari, Gurpreet Kaur, Mark Sunohara, David R. Lapen, and Heather McNairn. 2020. "Using Artificial Neural Networks and Remotely Sensed Data to Evaluate the Relative Importance of Variables for Prediction of Within-Field Corn and Soybean Yields" Remote Sensing 12, no. 14: 2230. https://doi.org/10.3390/rs12142230

Kross, A., Znoj, E., Callegari, D., Kaur, G., Sunohara, M., Lapen, D. R., & McNairn, H. (2020). Using Artificial Neural Networks and Remotely Sensed Data to Evaluate the Relative Importance of Variables for Prediction of Within-Field Corn and Soybean Yields. Remote Sensing, 12(14), 2230. https://doi.org/10.3390/rs12142230