Dan Børge Jensen

Dan Børge Jensen

Associate Professor

Member of:

    ORCID: 0000-0002-9437-0605

    Publication year:
    All
    1 - 5 out of 5Page size: 10
    1. 2015
    2. Published

      Bayesian prediction of mastitis using sensor data routinely collected in dairy herds

      Jensen, Dan Børge & Devries, A., Aug 2015, Book of Abstracts of the 66th Annual Meeting of the European Federation of Animal Science. p. 297 1 p.

      Research output: Chapter in Book/Report/Conference proceeding › Conference abstract in proceedings › Research › peer-review

    3. Published

      The intelligent pig barn

      Kristensen, Anders Ringgaard & Jensen, Dan Børge, 29 Apr 2015, Improving Pig Welfare - what are the ways forward?: International conference on pig welfare. p. 34-37 4 p.

      Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research

    4. Published

      A multi-dimensional dynamic linear model for monitoring slaughter pig production

      Jensen, Dan Børge, Cornou, C., Toft, N. & Kristensen, Anders Ringgaard, 2015.

      Research output: Contribution to conference › Paper › Research › peer-review

    5. Published

      A multi-dimensional dynamic linear model for monitoring growing pigs

      Jensen, Dan Børge, 2015, Up to date with pig research: book of presentations of the 2nd CPH Pig seminar. Faculty of Health and Medical Sciences, University of Copenhagen, p. 55-58 4 p.

      Research output: Chapter in Book/Report/Conference proceeding › Conference abstract in proceedings › Research

    6. Published

      Temperature as a predictor of fouling and diarrhea in Slaughter pigs

      Jensen, Dan Børge, Toft, N. & Kristensen, Anders Ringgaard, 2015, Book of abstracts of the 66th Annual Meeting of the European Association for Animal Production: Warsaw, Poland, 31 August - 4 September 2015. Wageningen Academic Publishers, p. 303 1 p. Poster 14

      Research output: Chapter in Book/Report/Conference proceeding › Conference abstract in proceedings › Research › peer-review

    ID: 44182188