Towards Autonomous Crop Monitoring: Inserting Sensors in Cluttered Environments
Author:
Affiliation:
1. Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA
2. Department of Computer Science, Harvard University, Cambridge, MA, USA
3. Department of Agronomy, Iowa State University, Ames, IA, USA
Funder
NSF
NSF/USDA NIFA AIIRA AI Research Institute
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
https://ieeexplore.ieee.org/ielam/7083369/10504377/10494888-aam.pdf
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1. Actuators and Sensors for Application in Agricultural Robots: A Review
2. Point-of-use sensors and machine learning enable low-cost determination of soil nitrogen
3. M2F-Net: A Deep Learning-Based Multimodal Classification with High-Throughput Phenotyping for Identification of Overabundance of Fertilizers
4. A review on plant high-throughput phenotyping traits using UAV-based sensors
5. Selective spraying of grapevines for disease control using a modular agricultural robot
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