Felix B. Fritschi

Orcid: 0000-0003-0825-6855

According to our database1, Felix B. Fritschi authored at least 15 papers between 2017 and 2022.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Other 

Links

On csauthors.net:

Bibliography

2022
Estimating Crop Seed Composition Using Machine Learning from Multisensory UAV Data.
Remote. Sens., 2022

PRMI: A Dataset of Minirhizotron Images for Diverse Plant Root Study.
CoRR, 2022

2021
Spatio-Temporal Reconstruction and Visualization of Plant Growth for Phenotyping.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

Crop Yield Prediction using Satellite/Uav Synergy and Machine Learning.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021

2020
Crop Monitoring Using Satellite/UAV Data Fusion and Machine Learning.
Remote. Sens., 2020

Root identification in minirhizotron imagery with multiple instance learning.
Mach. Vis. Appl., 2020

Overcoming small minirhizotron datasets using transfer learning.
Comput. Electron. Agric., 2020

LabelStoma: A tool for stomata detection based on the YOLO algorithm.
Comput. Electron. Agric., 2020

Weakly Supervised Minirhizotron Image Segmentation with MIL-CAM.
Proceedings of the Computer Vision - ECCV 2020 Workshops, 2020

2019
UAV-Based High Resolution Thermal Imaging for Vegetation Monitoring, and Plant Phenotyping Using ICI 8640 P, FLIR Vue Pro R 640, and thermoMap Cameras.
Remote. Sens., 2019

Remote Sensing of Explosives-Induced Stress in Plants: Hyperspectral Imaging Analysis for Remote Detection of Unexploded Threats.
Remote. Sens., 2019

VisND: A Visualization Tool for Multidimensional Model of Canopy.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

2018
A New 4D-RGB Mapping Technique for Field-Based High-Throughput Phenotyping.
Proceedings of the British Machine Vision Conference 2018, 2018

2017
Vinobot and Vinoculer: Two Robotic Platforms for High-Throughput Field Phenotyping.
Sensors, 2017

Automated Classification of Wrinkle Levels in Seed Coat Using Relevance Vector Machine.
Proceedings of the 2017 IEEE Applied Imagery Pattern Recognition Workshop, 2017


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