Towards automatic farrowing monitoring-A Noisy Student approach for improving detection performance of newborn piglets.

Nowadays, video monitoring of farrowing and automatic video evaluation using Deep Learning have become increasingly important in farm animal science research and open up new possibilities for addressing specific research questions like the determination of husbandry relevant indicators. A robust detection performance of newborn piglets is essential for reliably monitoring the farrowing process and to access important information about the welfare status of the sow and piglets. Although object detection algorithms are increasingly being used in various scenarios in the field of livestock farming, their usability for detecting newborn piglets has so far been limited.

Acceptance and Feasibility of a Guideline for the Animal Welfare Assessment of Fattening Pigs from Farmers' Point of View.

The welfare of farm animals is being increasingly discussed in society and politics. To evaluate animal welfare, indicator systems are often used. Such a system has been developed by the German Association for Technology and Structures in Agriculture and suggested in the publication "Animal Welfare Indicators: Practical Guide-Pigs".