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Leveraging latent representations for milk yield prediction and interpolation using deep learning

  • Published:2020-08 Issue: Volume:175 Page:105600
  • ISSN:0168-1699
  • Container-title:Computers and Electronics in Agriculture
  • language:en
  • Short-container-title:Computers and Electronics in Agriculture

Author:

Liseune Arno,Salamone Matthieu,Van den Poel Dirk,Van Ranst Bonifacius,Hostens Miel

Publisher

Elsevier BV

Subject

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

Reference32 articles.

1. Method for short-term prediction of milk yield at the quarter level to improve udder health monitoring;Adriaens;J. Dairy Sci.,2018

2. Accounting for covariances among test day milk yields in dairy cows;Ali;Canadian J. Anim. Sci.,1987

3. Generalized denoising auto-encoders as generative models;Bengio;Advances in Neural Information Processing Systems,2013

4. Random forests;Breiman;Mach. Learn.,2001

5. Comparative efficiency of artificial neural networks and multiple linear regression analysis for prediction of first lactation 305-day milk yield in Sahiwal cattle;Dongre;Livestock Sci.,2012

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