Machine Learning for High-Throughput Stress Phenotyping in Plants von Singh, Arti, Ganapathysubramanian, Baskar, Singh, Asheesh Kumar, Sarkar, Soumik

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An explainable deep machine vision framework for plant stress phenotyping von Ghosal, Sambuddha, Blystone, David, Singh, Asheesh K., Ganapathysubramanian, Baskar, Singh, Arti, Sarkar, Soumik

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Plant disease identification using explainable 3D deep learning on hyperspectral images von Nagasubramanian, Koushik, Jones, Sarah, Singh, Asheesh K, Sarkar, Soumik, Singh, Arti, Ganapathysubramanian, Baskar

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Crop yield prediction integrating genotype and weather variables using deep learning von Shook, Johnathon, Gangopadhyay, Tryambak, Wu, Linjiang, Ganapathysubramanian, Baskar, Sarkar, Soumik, Singh, Asheesh K

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Machine Learning Approach for Prescriptive Plant Breeding von Parmley, Kyle A., Higgins, Race H., Ganapathysubramanian, Baskar, Sarkar, Soumik, Singh, Asheesh K.

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A deep learning framework to discern and count microscopic nematode eggs von Akintayo, Adedotun, Tylka, Gregory L., Singh, Asheesh K., Ganapathysubramanian, Baskar, Singh, Arti, Sarkar, Soumik

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Hydrogel-based transparent soils for root phenotyping in vivo von Ma, Lin, Shi, Yichao, Siemianowski, Oskar, Yuan, Bin, Egner, Timothy K., Mirnezami, Seyed Vahid, Lind, Kara R., Ganapathysubramanian, Baskar, Venditti, Vincenzo, Cademartiri, Ludovico

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Deep Learning for Plant Stress Phenotyping: Trends and Future Perspectives von Singh, Asheesh Kumar, Ganapathysubramanian, Baskar, Sarkar, Soumik, Singh, Arti

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A real-time phenotyping framework using machine learning for plant stress severity rating in soybean von Naik, Hsiang Sing, Zhang, Jiaoping, Lofquist, Alec, Assefa, Teshale, Sarkar, Soumik, Ackerman, David, Singh, Arti, Singh, Asheesh K, Ganapathysubramanian, Baskar

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Hyperspectral band selection using genetic algorithm and support vector machines for early identification of charcoal rot disease in soybean stems von Nagasubramanian, Koushik, Jones, Sarah, Sarkar, Soumik, Singh, Asheesh K, Singh, Arti, Ganapathysubramanian, Baskar

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Genome-wide association analysis of seedling root development in maize (Zea mays L.) von Pace, Jordon, Gardner, Candice, Romay, Cinta, Ganapathysubramanian, Baskar, Lübberstedt, Thomas

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A vorticity-based criterion to characterise leading edge dynamic stall onset von Sudharsan, Sarasija, Ganapathysubramanian, B., Sharma, A.

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Predicting county-scale maize yields with publicly available data von Jiang, Zehui, Liu, Chao, Ganapathysubramanian, Baskar, Hayes, Dermot J., Sarkar, Soumik

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A Case Study of Deep Reinforcement Learning for Engineering Design: Application to Microfluidic Devices for Flow Sculpting von Lee, Xian Yeow, Balu, Aditya, Stoecklein, Daniel, Ganapathysubramanian, Baskar, Sarkar, Soumik

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A framework for parametric design optimization using isogeometric analysis von Herrema, Austin J., Wiese, Nelson M., Darling, Carolyn N., Ganapathysubramanian, Baskar, Krishnamurthy, Adarsh, Hsu, Ming-Chen

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An octree-based immersogeometric approach for modeling inertial migration of particles in channels von Xu, Songzhe, Gao, Boshun, Lofquist, Alec, Fernando, Milinda, Hsu, Ming-Chen, Sundar, Hari, Ganapathysubramanian, Baskar

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Electronic, redox, and optical property prediction of organic π-conjugated molecules through a hierarchy of machine learning approaches von Bhat, Vinayak, Sornberger, Parker, Pokuri, Balaji Sesha Sarath, Duke, Rebekah, Ganapathysubramanian, Baskar, Risko, Chad

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Challenges and Opportunities in Machine-Augmented Plant Stress Phenotyping von Singh, Arti, Jones, Sarah, Ganapathysubramanian, Baskar, Sarkar, Soumik, Mueller, Daren, Sandhu, Kulbir, Nagasubramanian, Koushik

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Immersogeometric analysis of moving objects in incompressible flows von Xu, Songzhe, Xu, Fei, Kommajosula, Aditya, Hsu, Ming-Chen, Ganapathysubramanian, Baskar

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UAS-Based Plant Phenotyping for Research and Breeding Applications von Guo, Wei, Carroll, Matthew E, Singh, Arti, Swetnam, Tyson L, Merchant, Nirav, Sarkar, Soumik, Singh, Asheesh K, Ganapathysubramanian, Baskar

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