This award goes to ALL authors and I must send out ❤️ and 🙏 to Martin (@martweig) who really is the 🧠 behind CARE and Uwe (@uschmidt83) without who the quality and usability of CSBDeep would not be anywhere close to what it is. @PavelTomancak helped us write a GOOD paper, and…
Congratulations to @florianjug for being awarded the 2023 ICBS Frontiers of Science award! The International Congress for Basic Science honors top research with an emphasis on achievements from the past 5 years which are both excellent and of outstanding scholarly value.
GitHub stats give adequate credits to the creators of this truly wonderful resource: @frauzufall (lion share) and @bewilh.
github.com/CSBDeep/CSBDeep_f…
Thanks to you two and also to all other (beyond Fiji) CSBDeep heroes!
If you’re looking for a friendly interface to interact with code, notebooks such as @ProjectJupyter or @GoogleColab notebooks are a great resource.
#CSBDeep, #ZerocostDL4Mic and #CellPose prepared ready-to-use notebooks to test and/or train neural networks.
Thank you @pushkal_sharma
I'm afraid that you'll need to train/fine-tune a model, BUT that's not a problem any more if you have some annotated images: #ZeroCostDL4Mic is your solution. Also you can try to train #DenoiSeg in the #CSBDeep plugin for ImageJ, or use #Ilastik, #Yapic
The #i2k2020 phenotype: 10:30 PM roaming around the island, having a beer, updating CUDA, training a network and labelling images. Good thing I expected nothing less...
#CSBDeep#WeAreStarDist
Thanks Pedro! It's really fun and the DL approaches are amazingly powerful. Especially the #CARE networks by @martweig. The implementation in #ZeroCostDL4Mic and the #CSBDeep plugin in #Fiji are super nice to use! Thanks to the entire #OpenSource#DeepLearning community!
New back-to-back releases of our DL python packages csbdeep and stardist. Among many other things, now allows for using tf2, stitched predictions on large 2D images, and importing 3D stardist results in @blender_org
:) kudos to @uschmidt83!