Bayesian aggregation improves traditional single image crop classification approaches

Original title

Bayesian aggregation improves traditional single image crop classification approaches

Russian translation

Байесовское агрегирование улучшает традиционные подходы к классификации культур по одиночному изображению

Translation status: source

Evidence statuses

relation_layer

D — context

relation_confidence

2 — strong

relevance_status

Included

body_status

Local full text verified

doi_status

Confirmed

access_status

Metadata only

expert_review

Included

verification_status

Body verified

Details

year

2020

type

Conference paper

venue

ICLR 2020 Workshop on Computer Vision for Agriculture (CV4A); arXiv:2004.03468

DOI

10.48550/arxiv.2004.03468

People

• Ivan Matvienko
• Гасанов Михаил
• Anna Petrovskaia
• Raghavendra Belur Jana
• Mariia Pukalchik
• Ivan Oseledets

Topics

• Biomass and yield
• Calibration and validation
• Forecasting and decision support
• GIS and remote sensing

Sources

• arXiv author manuscript: Bayesian single-image crop classification workshop version, 2020

External links

• https://arxiv.org/abs/2004.03468
• https://doi.org/10.48550/arXiv.2004.03468