Assessing kernel processing score of harvested corn silage in real-time using image analysis and machine learning-Reference-Cited by-同舟云学术

Assessing kernel processing score of harvested corn silage in real-time using image analysis and machine learning

Published:2022-12 Issue: Volume:203 Page:107415
ISSN:0168-1699
Container-title:Computers and Electronics in Agriculture
language:en
Short-container-title:Computers and Electronics in Agriculture

Author:

Rocha Eduardo M.C.,Drewry Jessica L.,Willett Rebecca M.,Luck Brian D.^ORCID

Publisher

Elsevier BV

Subject

Horticulture,Computer Science Applications,Agronomy and Crop Science,Forestry

Reference33 articles.

1. Machine learning regression techniques for the silage maize yield prediction using time-series images of landsat 8 OLI;Aghighi;IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens.,2018

2. ASABE, 2021. Moisture measurement - forages. (ANSI/ASAE S358.3 May2012 (R2021)). St. Joseph, Mich.: ASABE. Retrieved from https://elibrary.asabe.org/standards.asp.

3. ASABE, 2022. Method of determining and expressing particle size of chopped forage materials by screening (ANSI/ASAE S424.1 Mar1992 (R2022)). St. Joseph, Mich.: ASABE. Retrieved from https://elibrary.asabe.org/standards.asp.

4. Bohrer, S., 2018. [Personal Communication]. Phone interview.

5. Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., Fei-Fei, L., 2009. ImageNet: A Large-Scale Hierarchical Image Database. In: CVPR 09.

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