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AIFARMS TEAM PUBLICATIONS

Citations

[1]
V. Adve, “Beyond ML in Agricultural Intelligence,” Virtual, 21-Oct-2021.
[1]
M. Khanna, “Economic Incentives for Robotic Weed Control,” Virtual - University of Bonn, 24-Sep-2021 [Online]. Available: https://www.phenorob.de/
[1]
R. Finger, R. Huber, Y. Wang, and M. Khanna, “Digital innovations for more sustainable agricultural landscapes,” Viirtual - Berlin, 20-Sep-2021.
[1]
A. Leakey, “Phenotyping stomatal anatomy and function,” Virtual, Sep-2021.
[1]
M. Khanna, “Digital Transformation for a Sustainable Agriculture in the US: Opportunities and Challenges,” Virtual, 29-Aug-2021 [Online]. Available: https://www.cgiar.org/news-events/event/international-conference-of-agricultural-economists-icae-2021/
[1]
J. Wu and J. He, “Indirect Invisible Poisoning Attacks on Domain Adaptation,” SIGKDD Conference on Knowledge Discovery & Data Mining, pp. 1852–1862, Aug. 2021, doi: https://doi.org/10.1145/3447548.3467214.
[1]
T. Williams and A. Green-Miller, “Engineered Resilience in Livestock for Improved Animal Welfare,” Louisville, KY, 16-Jul-2021 [Online]. Available: https://www.asas.org/meetings/annual-2021
[1]
J. Xie et al., “Optical topometry and machine learning to rapidly phenotype stomatal patterning traits for maize QTL mapping,” Plant Physiology, vol. kiab299, Jul. 2021, doi: https://doi.org/10.1093/plphys/kiab299.
[1]
D. Northrup, B. Basso, M. Q. Wang, C. L. S. Morgan, and P. Benfey, “Novel technologies for emission reduction complement conservation agriculture to achieve negative emissions from row-crop production,” Proceedings of the National Academy of Sciences, vol. 118, no. 28, Jul. 2021, doi: https://doi.org/10.1073/pnas.2022666118.
[1]
A. Shirke et al., “Tracking Grow-Finish Pigs Across Large Pens Using Multiple Cameras,” Portugal (Virtual), Jul-2021.
[1]
A. Schwing, “AIFARMS: Artificial Intelligence for Future Agricultural Resilience, Management and Sustainability,” CVPR 2021 - Virtual, 19-Jun-2021.
[1]
V. Adve, “AIFARMS: Artificial Intelligence for Future Agricultural Resilience, Management and Sustainability,” Virtual, 03-Jun-2021.
[1]
T.-T. Hu, J. Wang, R. A. Yeh, and A. G. Schwing, “SAIL-VOS 3D: A Synthetic Dataset and Baselines for Object Detection and 3D Mesh Reconstruction From Video Data,” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1418–1428, Jun. 2021 [Online]. Available: https://arxiv.org/abs/2105.08612
[1]
C. Graber, G. Tsai, M. Firman, G. Brostow, and A. G. Schwing, “Panoptic Segmentation Forecasting,” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12517–12526, Jun. 2021 [Online]. Available: https://arxiv.org/abs/2104.03962
[1]
Z. Ren, I. Misra, A. G. Schwing, and R. Girdhar, “3D Spatial Recognition Without Spatially Labeled 3D,” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 13204–13213, Jun. 2021 [Online]. Available: https://arxiv.org/abs/2105.06461
[1]
A. Shirke et al., “Tracking Grow-Finish Pigs Across Large Pens Using Multiple Cameras,” Virtual, Jun-2021 [Online]. Available: https://cvpr2021.thecvf.com/
[1]
B. Basso, “Precision conservation for a changing climate,” Nature, vol. 2, pp. 322–323, May 2021, doi: https://doi.org/10.1038/s43016-021-00283-z.
[1]
A. Leakey, “Overcoming bottlenecks in field-based root phenotyping using thousands of minirhizotrons,” Virtual, May-2021.
[1]
A. Maestrini and B. Basso, “Subfield crop yields and temporal stability in thousands of US Midwest fields,” Precision Agriculture, May 2021 [Online]. Available: https://link.springer.com/article/10.1007/s11119-021-09810-1
[1]
P. Zhuang, O. Koyejo, and A. G. Schwing, “Enjoy Your Editing: Controllable GANs for Image Editing via Latent Space Navigation,” International Conference on Learning Representations, May 2021 [Online]. Available: https://arxiv.org/abs/2102.01187
[1]
V. Adve, “Computational Needs for the AIFARMS National AI Institute,” 07-Apr-2021.
[1]
A. Leakey, “The Phenomics of Stomata and Water Use Efficiency in C4 crops,” Virtual, Apr-2021.
[1]
B. JIng, H. Tong, and Y. Zhu, “Network of Tensor Time Series,” Proceedings of the Web Conference 2021, pp. 2425–2437, Apr. 2021, doi: https://doi.org/10.1145/3442381.3449969.
[1]
V. Adve, “AIFARMS: Artificial Intelligence for Future Agricultural Resilience, Management and Sustainability,” Virtual, 23-Mar-2021.
[1]
B. Basso, R. Martinez-Feria, L. Rill, and J. Ritchie, “Contrasting long-term temperature trends reveal minor changes in projected potential evapotranspiration in the US Midwest,” Nature Communications, vol. 12, p. 1476, Mar. 2021, doi: https://doi.org/10.1038/s41467-021-21763-7.
[1]
A. Leakey, “The Phenomics of Stomata and Water Use Efficiency in C4 crops,” Virtual, Mar-2021.
[1]
T. Williams, “The Art and Science of Black Farming,” Virtual, 27-Feb-2021.
[1]
E. Ainsworth, “Using hyperspectral reflectance to estimate and map photosynthesis in a soybean NAM population,” Virtual, Feb-2021.
[1]
A. Leakey, “The Phenomics of Stomata and Water Use Efficiency in C4 crops,” Virtual, Feb-2021.
[1]
B. Basso, “Digital Agriculture to Reduce Nitrogen Losses across the U.S. Corn Belt,” Virtual, 2021.
[1]
B. Basso et al., “Exploring a Dynamic Soil INformation System: Proceedings of a Workshop,” Washington DC, 2021.
[1]
A. Leakey, “The Phenomics of Stomata and Water Use Efficiency in C4 crops,” Virtual, Dec-2020.
[1]
I.-J. Liu, R. A. Yeh, and A. G. Schwing, “High-Throughput Synchronous Deep RL,” NeurIPS 2020, Dec. 2020 [Online]. Available: https://ioujenliu.github.io/HTS-RL/
[1]
V. Adve, “Why Digital Agriculture is Fertile Ground for Software Systems Research,” SPLASH 2020, the ACM SIGPLAN conference on Systems, Programming, Languages, and Applications: Software for Humanity, 19-Nov-2020.
[1]
V. Adve, “AIFARMS: Artificial Intelligence for Future Agricultural Resilience, Management and Sustainability,” Virtual, 10-Nov-2020.
[1]
M. Khanna, “Digital Transformation of the Agricultural Sector: Pathways, Drivers and Policy Implications,” Applied Economic Perspectives and Policy, Oct. 2020, doi: https://doi.org/10.1002/aepp.13103.
[1]
V. Adve, “AIFARMS: Artificial Intelligence for Future Agricultural Resilience, Management and Sustainability,” Virtual, 07-Oct-2020.
[1]
A. Leakey, “The Phenomics of Stomata and Water Use Efficiency in C4 crops,” Virtual, Oct-2020.
[1]
Z. Ren, R. A. Yeh, and Schwing, “Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning,” NeurIPS 2020, vol. 2, Oct. 2020 [Online]. Available: https://arxiv.org/abs/2007.01293
[1]
B. Basso and J. Antle, “Digital agriculture to design sustainable agricultural systems,” Nature Sustainability, vol. 3, pp. 254–256, Apr. 2020 [Online]. Available: https://www.nature.com/articles/s41893-020-0510-0
[1]
R. Sun, T. Fang, and A. G. Schwing, “Towards a Better Global Loss Landscape of GANs,” Neur IPS 2020, 2020 [Online]. Available: https://proceedings.neurips.cc/paper/2020/file/738a6457be8432bab553e21b4235dd97-Paper.pdf