# Sierra Young

**Type:** Researchers  
**Canonical URL:** https://scholariq.org/researchers/sierra-young/

## Facts

| Field | Value |
| --- | --- |
| Citations | 1,262 |
| Field | Smart Agriculture and AI |
| h-index | 16 |
| i10-index | 25 |
| Last Known Institution | Utah State University |
| OpenAlex ID | https://openalex.org/A5033783807 |
| ORCID iD | 0000-0001-9146-1088 |
| Works | 65 |

## Researcher papers

- [A survey of public datasets for computer vision tasks in precision agriculture](https://scholariq.org/papers/a-survey-of-public-datasets-for-computer-vision-tasks-in-precision-agriculture/)
- [Performance evaluation of deep transfer learning on multi-class identification of common weed species in cotton production systems](https://scholariq.org/papers/performance-evaluation-of-deep-transfer-learning-on-multi-class-identification/)
- [Design and field evaluation of a ground robot for high-throughput phenotyping of energy sorghum](https://scholariq.org/papers/design-and-field-evaluation-of-a-ground-robot-for-high-throughput-phenotyping-of/)
- [Review of Human–Machine Interfaces for Small Unmanned Systems With Robotic Manipulators](https://scholariq.org/papers/review-of-human-machine-interfaces-for-small-unmanned-systems-with-robotic/)
- [Robust plant segmentation of color images based on image contrast optimization](https://scholariq.org/papers/robust-plant-segmentation-of-color-images-based-on-image-contrast-optimization/)
- [Detection of crop diseases using enhanced variability imagery data and convolutional neural networks](https://scholariq.org/papers/detection-of-crop-diseases-using-enhanced-variability-imagery-data-and/)
- [Towards rapid weight assessment of finishing pigs using a handheld, mobile RGB-D camera](https://scholariq.org/papers/towards-rapid-weight-assessment-of-finishing-pigs-using-a-handheld-mobile-rgb-d/)
- [Opportunities for Robotic Systems and Automation in Cotton Production](https://scholariq.org/papers/opportunities-for-robotic-systems-and-automation-in-cotton-production/)
- [Hyperspectral Imaging With Machine Learning to Differentiate Cultivars, Growth Stages, Flowers, and Leaves of Industrial Hemp (Cannabis sativa L.)](https://scholariq.org/papers/hyperspectral-imaging-with-machine-learning-to-differentiate-cultivars-growth/)
- [Predicting foliar nutrient concentrations and nutrient deficiencies of hydroponic lettuce using hyperspectral imaging](https://scholariq.org/papers/predicting-foliar-nutrient-concentrations-and-nutrient-deficiencies-of/)

## Researcher topics

- [Smart Agriculture and AI](https://scholariq.org/topics/smart-agriculture-and-ai/)
- [Spectroscopy and Chemometric Analyses](https://scholariq.org/topics/spectroscopy-and-chemometric-analyses/)
- [Remote Sensing in Agriculture](https://scholariq.org/topics/remote-sensing-in-agriculture/)
- [Remote Sensing and LiDAR Applications](https://scholariq.org/topics/remote-sensing-and-lidar-applications/)
- [Water Quality Monitoring Technologies](https://scholariq.org/topics/water-quality-monitoring-technologies/)

## Researcher university

- [Utah State University](https://scholariq.org/institutions/utah-state-university/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.