Sierra Young

Detection of crop diseases using enhanced variability imagery data and convolutional neural networks

COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2.

Hyperspectral Imaging With Machine Learning to Differentiate Cultivars, Growth Stages, Flowers, and Leaves of Industrial Hemp (Cannabis sativa L.)

FRONTIERS IN PLANT SCIENCE, 2.

Robust plant segmentation of color images based on image contrast optimization

COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2.

Ten Simple Rules for Researchers Who Want to Develop Web Apps

Saia, S., Nelson, N., Young, S., Parham, S., & Vandegrift, M. (2022, January 31). (Vol. 1). Vol. 1.

Ten simple rules for researchers who want to develop web apps

PLOS Computational Biology.

FRONTIER: AUTONOMY IN DETECTION, ACTUATION, AND PLANNING FOR ROBOTIC WEEDING SYSTEMS

TRANSACTIONS OF THE ASABE, 64(2), 557–563.

HYPERSPECTRAL IMAGING WITH COST-SENSITIVE LEARNING FOR HIGH-THROUGHPUT SCREENING OF LOBLOLLY PINE (PINUS TAEDA L.) SEEDLINGS FOR FREEZE TOLERANCE

TRANSACTIONS OF THE ASABE.

Hyperspectral Imaging Combined with Machine Learning for the Detection of Fusiform Rust Disease Incidence in Loblolly Pine Seedlings

REMOTE SENSING, 13(18), 3595.

Opportunities for Robotic Systems and Automation in Cotton Production

Barnes, E., Morgan, G., Hake, K., Devine, J., Kurtz, R., Ibendahl, G., … Holt, G. (2021, June). AGRIENGINEERING, Vol. 6.

Prediction of Freeze Damage and Minimum Winter Temperature of the Seed Source of Loblolly Pine Seedlings Using Hyperspectral Imaging

FOREST SCIENCE, 67(3), 321–334.

Spectral light-reflection data dimensionality reduction for timely detection of yellow rust

Precision Agriculture, 22(1), 267–286.

The Effects of Interface Views on Performing Aerial Telemanipulation Tasks Using Small UAVs

Young, S. N., Lanciloti, R. J., & Peschel, J. M. (2021, April 8). INTERNATIONAL JOURNAL OF SOCIAL ROBOTICS, Vol. 4.

A process‐based approach to attribution of historical streamflow decline in a data‐scarce and human‐dominated watershed

Hydrological Processes.

A survey of public datasets for computer vision tasks in precision agriculture

Computers and Electronics in Agriculture, 178, 105760.

Review of Human–Machine Interfaces for Small Unmanned Systems With Robotic Manipulators

IEEE Transactions on Human-Machine Systems, 50(2), 131–143.

A Framework for Evaluating Field-Based, High-Throughput Phenotyping Systems: A Meta-Analysis

SENSORS, 19(16), 3582.

Design and field evaluation of a ground robot for high-throughput phenotyping of energy sorghum

Precision Agriculture, 20(4), 697–722.

Robot-Assisted Measurement for Hydrologic Understanding in Data Sparse Regions

Water, 9(7), 494.

High-precision control of tracked field robots in the presence of unknown traction coefficients

Kayacan, E., Young, S. N., Peschel, J. M., & Chowdhary, G. Journal of Field Robotics, 0(0).