High-throughput phenotyping

By Natalie de Souza. 2009

91 citations recorded by the source corpus.

Subfields: Biophysics, Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biophysics

1. Tyson E. Ochsner
2. Andres Patrignani

In Molecular Biology

1. Wolfgang Stammer
2. Kristian Kersting
3. Tyson E. Ochsner
4. Patrick Schramowski
5. Andres Patrignani

Citations in the corpus

• Making deep neural networks right for the right scientific reasons by interacting with their explanations (2020, background): “To demonstrate the significance of XIL, we demonstrate XIL for deep plant phenotyping and plant disease detection, a growing and relevant field of research [55, 56, 57, 58, 59, 60].”
• Canopeo: A Powerful New Tool for Measuring Fractional Green Canopy Cover (2015, methodology): “The Canopeo classification approach demonstrated robust performance even for imperfect images such as when the user’s feet or the camera monopod’s shadow were present in the images (e.g., Sharma and Ritchie, 2015).”