CRII: RI: Uncertainty Estimation and Robustness in Hierarchical Classification — NSF Award to Illinois Institute of Technology (IL
Hierarchical classification is the task of categorizing items belonging to a structured hierarchy. Examples of this task include tracking of animals for monitoring variability in species and pests in precision agriculture. Reliable automation of hierarchical classification has the potential to accelerate sustainability
| Award title | CRII: RI: Uncertainty Estimation and Robustness in Hierarchical Classification |
|---|---|
| Award ID | 2451714 |
| Awardee | Illinois Institute of Technology |
| City | CHICAGO |
| State | IL |
| Amount obligated | $172,913 |
| Principal investigator | Yutong Wang |
| Program | Robust Intelligence |
| Start date | 06/15/2025 |
| Abstract | Hierarchical classification is the task of categorizing items belonging to a structured hierarchy. Examples of this task include tracking of animals for monitoring variability in species and pests in precision agriculture. Reliable automation of hierarchical classification has the potential to accelerate sustainability efforts and boost agricultural productivity. Machine learning is increasingly being used as an automation tool in ecology and agriculture. However, to fully realize the potential |
| Source | NSF Awards |
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