๐ฎ Check out the demo โ train on three clients using the BCSS dataset! ๐ Integrated AIM support makes logging and visualizing results super easy.
๐ Theoden is evolving! Stay tuned for regular updates as we continue to push the boundaries! ๐๐ฉโ๐ฌ๐จโ๐ป #FederatedLearning
Tackling the intricate world of cross-silo federated learning in medical data ๐ฉบ๐ป, Theoden is your go-to research framework!
โจ Flexible: Easily incorporate new data, models, and methods without framework tweaks! ๐ ๏ธ
Thank you @BMBF_Bund for the support.
I am happy to announce that I have graduated with honors from the @TUDarmstadt with a Master's degree in Computer Science and am now starting my #PhD at #MECLabTUDA of @anirbanakash.
I will be researching in the field of #digitalpathology and decentralized learning.
It is in great fear, not knowing what mighty artefact may appear, wield FrOoDo and evaluate artefacts in an easy and adaptable way.๐ฌ๐งซ
So if you are in London at @The_CBIAS:
Let's meet and chat.
#MECLabTUDA#CBIAS2022#microscopy
๐งฉhttps://t.co/fHczBAOiQg
Speak friend and clone the github repo for the latest feature update.
To detect untrained creatures from a different age FrOoDo now supports classification and many more.
@JonStie, @anirbanakash, @CS_TUDarmstadt
#MECLabTUDA
๐งฉhttps://t.co/fHczBAwHYI
๐ https://t.co/CvwMM2M6PL
Thank you to the Hoch3 team to cover our research on #surgical#ai in such a balanced fashion!
A team effort from #MECLAbTUDA @CS_TUDarmstadt members: @le_hekr, @kueglerd, @mofuchs1, Johannes Fauser, @DhritimaanDas1 and many more.
๐ฅThe shire is burning silently. So FrOoDo goes to MOOrDor.๐ฅ
FrOoDo is a Framework for Out-of-Distribution Detection. We demonstrate its usefulness for computational pathology.
With @JonStie, @y_tolkach & @anirbanakash#MECLabTUDA, @CS_TUDarmstadt
๐งฉhttps://t.co/fHczBAwHYI