24 Photos and videos
24 Feb 2023
If you're interested in the details of our #StarDist-based submission to the 2022 CoNIC challenge, we finally released the code.
github.com/stardist/stardist…
29 Mar 2022
How well does #StarDist work on histopathology images? Pretty well! Our StarDist approach (with @uschmidt83) just won the nuclei seg/class task of the ISBI 2022 CoNIC challenge! 🎉
Paper: arxiv.org/abs/2203.02284
conic-challenge.grand-challe…
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Uwe Schmidt retweeted
Together with the wonderful collaborators and community partners, we are happy to finally present the BioImage Model Zoo at bioimage.io, now described in biorxiv.org/content/10.1101/….
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Uwe Schmidt retweeted
29 Mar 2022
How well does #StarDist work on histopathology images? Pretty well! Our StarDist approach (with @uschmidt83) just won the nuclei seg/class task of the ISBI 2022 CoNIC challenge! 🎉
Paper: arxiv.org/abs/2203.02284
conic-challenge.grand-challe…
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Uwe Schmidt retweeted
30 Jan 2022
I get a lot of reviews that say my work is not novel and I bet I'm not alone. It's always frustrating because I see novelty where the reviewer doesn't. Rather than rebut every critique, I've written a blog post to help reviewers think about novelty. perceiving-systems.blog/en/n…
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Uwe Schmidt retweeted
12 Jul 2021
Our new paper on "The Bayesian Learning Rule" is now on arXiv, where we provide a common learning-principle behind a variety of learning algorithms (optimization, deep learning, and graphical models).
arxiv.org/abs/2107.04562
Guess what, the principle is Bayesian. A very long🧵
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Uwe Schmidt retweeted
We just made a new stardist release, one of the bigger ones! Multi-class prediction, memory/runtime gains, and integration for the shiny new napari plugin :)
As usual, great colab with @uschmidt83 and many others: github.com/stardist/stardist…
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Uwe Schmidt retweeted
16 Dec 2020
Our FIB-SEM segmentation paper revealing part of the inner workings of insulin producing beta cells is out @JCellBiol! Great and super enjoyable teamwork under the lead of @Andi_Microscopy with @frauzufall @msolimena @HHMIJanelia @PLID_info @mpicbg @florianjug! @EPFL_Imaging
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Uwe Schmidt retweeted
11 Oct 2020
#I2K. 2x4 hour tutorials on #ImgLib2 #BDV #Numpy #Weka #CellPose #N5 #ImageJ2 #Ilastik #CLIJ #ImJoy #mManager #OMERO #ITK #SciView #CellProfiler #Icy #CSBDeep #CARE #StarDist #Noise2Void #BigStitcher Missing something? Respond to invite or apply. Oct 25th
janelia.org/you-janelia/conf…
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Uwe Schmidt retweeted
4 Oct 2020
Impressive accuracy of nucleus detection using #StarDist #QuPath in complex tissues - thanks to the developers for making these tools open source @petebankhead @QuPath @uschmidt83
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Uwe Schmidt retweeted
16 Sep 2020
Interested in using neural networks for estimating optical aberrations without collecting labelled ground truth data? Try out our approach - PhaseNet.
@martweig @uschmidt83 @TheGeneMyers
paper - osapublishing.org/oe/abstrac…
code - github.com/mpicbg-csbd/phase…
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Uwe Schmidt retweeted
30 Aug 2020
I'm a Research Software Engineer looking for challenging job opportunities since the lab is relocating in a couple of months. Dresden or remote. Experienced in open source development / image analysis / data visualization / deep learning / human computer interaction / ..
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Uwe Schmidt retweeted
26 Aug 2020
Now live @nature - on a new mechanism of nuclear remodelling in closed mitosis! If you missed the @biorxivpreprint or want to know what changed, thread to follow - once my co-authors & I finish our socially distanced pint 🍺 nature.com/articles/s41586-0…
Recent findings by @Dey_Gautam and colleagues suggest universal mechanisms may unite diverse mitotic strategies in eukaryotes, once thought to be completely distinct. @UCLLifeSciences @UCL_IPLS @nature
nature.com/articles/s41586-0…
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Reviewers automatically assume that simple is not novel. This is sheer laziness. Yes, it may be simple and obvious in retrospect, but someone had to have that insight first. Simple is good. Simple is robust, easy to implement and reproduce, broadly applicable, etc.
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Good benchmarks are important for progress in ML, but personally I’m more interested in research that explore new methods capable of doing things that existing SOTA methods simply fail at doing.
I also think pursuing such research is easier and more enjoyable than beating SOTA.
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Uwe Schmidt retweeted
14 Jul 2020
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!
14 Jul 2020
New Python releases for #CSBDeep and #StarDist! Lots of improvements under the hood, including support for TensorFlow 2. Joint effort with @martweig!
All changes:
github.com/CSBDeep/CSBDeep/r…
github.com/mpicbg-csbd/stard…
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14 Jul 2020
New Python releases for #CSBDeep and #StarDist! Lots of improvements under the hood, including support for TensorFlow 2. Joint effort with @martweig!
All changes:
github.com/CSBDeep/CSBDeep/r…
github.com/mpicbg-csbd/stard…
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Uwe Schmidt retweeted
28 May 2020
The curated list of Q&A's for our #StarDist webinar @NEUBIAS_COST can now be found at the forum: forum.image.sc/t/neubias-aca…
Webinar: youtube.com/watch?v=Amn_eHRG…
Big thanks to @ChiguireKun, @SuperResoluSian and esp. @uschmidt83!
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Uwe Schmidt retweeted
5 May 2020
Many papers have truly interesting ideas, but instead of presenting them clearly, they mix them with all kinds of other params and models to get SOTA, like:
ours = okay
ours baseline optimizer X = sota!!!
Can we just agree that a paper can be interesting w/o SOTA?
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