Hao Yang

Frontiers in Plant Science · 2017–2020

A researcher in the Science corpus: 4 papers; trusts 0 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Papers from Hao Yang's perspective

Ordered by how strongly the researchers Hao Yang trusts endorse each paper. Same corpus, a different order for every researcher.

1. Advantages of Hierarchical Linear Modeling.
2. Unmanned aerial systems for photogrammetry and remote sensing: A review
3. Thermal and Narrowband Multispectral Remote Sensing for Vegetation Monitoring From an Unmanned Aerial Vehicle (IEEE Transactions on Geoscience and Remote Sensing)
4. An Introduction to Variable and Feature Selection
5. Hierarchical Modeling and Analysis for Spatial Data
6. Development of a UAV-LiDAR System with Application to Forest Inventory (Remote Sensing)
7. Algorithms for Hyper-Parameter Optimization
8. Acquisition of NIR-Green-Blue Digital Photographs from Unmanned Aircraft for Crop Monitoring (Remote Sensing)
9. Pattern Recognition and Machine Learning
10. Estimating Biomass of Barley Using Crop Surface Models (CSMs) Derived from UAV-Based RGB Imaging (Remote Sensing)

Their papers

• A hierarchical interannual wheat yield and grain protein prediction model using spectral vegetative indices and meteorological data (2020) — 59 citations
• Modeling maize above-ground biomass based on machine learning approaches using UAV remote-sensing data (2019) — 374 citations
• Winter wheat yield estimation based on multi-source medium resolution optical and radar imaging data and the AquaCrop model using the particle swarm optimization algorithm (2017) — 140 citations
• Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives (2017) — 650 citations