Machine Learning and Image Analyses for Livestock Data
Hannah Cheren
February 22, 2022
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The vision of the Digital Livestock Lab is to create state-of-the-art
computer vision systems and the largest public database for livestock.
In this presentation from HTCondor Week 2021, Joao Dorea from the
Digital Livestock Lab explains how
high-throughput computing is used in the field of animal and dairy
sciences. Computer vision systems and sensors collect
animal-level phenotypic data on cows to make more optimized decisions
about what to do with each animal in terms of health, nutrition,
reproduction, and genetics. One challenge of doing this has to do
with the sheer size of data that is collected. Processing and
storing tens of thousands of images of cows requires significant
computational resources.
By utilizing HTCondor through a collaboration with the Center for High Throughput Computing, the Digital
Livestock Lab has been able to focus their time and money on the livestock.
Specialized to handle computational work that can be split into many pieces
and run in parallel, image analysis aligns well with the ideal HTCSS workload.
HTCondor allows them to run many jobs
and experiments congruently faster, opening the door to larger and larger data sets.
Being able to internalize numerous data sets in parallel has allowed the Digital Livestock Lab
to gain significant insight into livestock systems, all thanks to HTCondor
and collaborations with the faculty at the CHTC!
Read more about Joao Dorea and his research on the development of
high-throughput phenotyping technologies on his
homepage.