Frank Bai
Bio
Office: Weaver Laboratories 189
Education
B.E. Hydraulic and Hydropower Engineering China Agricultural University 2008
M.E. Agricultural soil and Water Engineering China Agricultural University 2010
Ph.D. Environmental Science and Technology Niigata University, Japan 2014
M.S. Computer Science University of Nebraska-Lincoln 2024
Area(s) of Expertise
Agricultural production is an essential part of human civilization, and we acknowledge the need for continuous improvements in productivity, efficiency, affordability, and sustainability. Despite advancements, there are still significant technology gaps in sensing, data processing, and application. Bai's research focuses on developing and applying advanced and reliable technologies in precision and digital agriculture to address these gaps and enhance system efficiency. His current interests include, but not limited to, high-throughput plant phenotyping for plant breeding and decision-making models for variable-rate field management. If you read his publications, you will find that most of them emerged from interdisciplinary collaboration between engineers and scientists, highlighting the importance of integrating diverse expertise to achieve innovative solutions in agriculture.
Publications
- Bagging Improves the Performance of Deep Learning-Based Semantic Segmentation with Limited Labeled Images: A Case Study of Crop Segmentation for High-Throughput Plant Phenotyping , Sensors (2024)
- Enhancing estimation of cover crop biomass using field-based high-throughput phenotyping and machine learning models , Frontiers in Plant Science (2024)
- High-throughput physiological phenotyping of crop evapotranspiration at the plot scale , Field Crops Research (2024)
- Up-regulation of non-photochemical quenching improves water use efficiency and reduces whole-plant water consumption under drought in Nicotiana tabacum , Journal of Experimental Botany (2024)
- AICropCAM: Deploying classification, segmentation, detection, and counting deep-learning models for crop monitoring on the edge , Computers and Electronics in Agriculture (2023)
- Crop Stress Sensing and Plant Phenotyping Systems: A Review , Smart Agriculture (2023)
- Diurnal Variation of Canopy NDVI in Maize and Soybean , Authorea Preprints (2023)
- Estimating crop stomatal conductance from RGB, NIR, and thermal infrared images , Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping VIII (2023)
- Goniometer in the air: Enabling BRDF measurement of crop canopies using a cable-suspended plant phenotyping platform , Biosystems Engineering (2023)
- Toward automated irrigation management with integrated crop water stress index and spatial soil water balance , Precision Agriculture (2023)