PhD Candidat @uni_bamberg_of ๐Ÿ“š | Exploring Robust Deep Learning for Medical Applications ๐Ÿฅ | Coffee Addict โ˜•๏ธ | Always Curious, Forever Learning ๐ŸŽ“ | โšฝ๏ธ๐Ÿฅพ

Joined January 2018
9 Photos and videos
๐Ÿš€ Looking for a novel method to enhance classification robustness under real-world label noise? Check out this work "An Embedding is Worth a Thousand Noisy Labels" led by @francescodis_ which was published in @TmlrOrg. ๐Ÿ“ openreview.net/forum?id=X3gSโ€ฆ ๐Ÿ™ github.com/francescodisalvo0โ€ฆ
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๐Ÿš€ Looking for a comprehensive benchmark for the MedMNIST database? Check out our latest paper, "Rethinking model prototyping through the MedMNIST dataset collection" now published open-access in @SciReports ๐Ÿ“ nature.com/articles/s41598-0โ€ฆ ๐Ÿ™ github.com/sdoerrich97/rethiโ€ฆ
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If you are at #BMVC2024 in Glasgow ๐Ÿด๓ ง๓ ข๓ ณ๓ ฃ๓ ด๓ ฟ and are interested in robustness for medical image diagnosis, feel free to drop by my oral tomorrow. ๐Ÿ—“๏ธ Wednesday, October 27, 2024 ๐Ÿ“ M3 ๐Ÿ•’ 11 AM ๐Ÿ–ผ๏ธ Unsupervised Feature Orthogonalization for Learning Distortion-Invariant Representations
๐Ÿš€ Excited to introduce: "Unsupervised Feature Orthogonalization for Learning Distortion-Invariant Representations", wich will be presented as an oral at the #RROW Workshop at #BMVC2024 ๐Ÿด๓ ง๓ ข๓ ณ๓ ฃ๓ ด๓ ฟ. ๐Ÿ“: arxiv.org/abs/2409.12276 ๐Ÿ™: github.com/sdoerrich97/unoraโ€ฆ ๐Ÿ‘ฅ: @francescodis_, @LedigChr
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If you're interested in histopathology and are attending #MICCAI2024 in ๐Ÿ‡ฒ๐Ÿ‡ฆ, feel free to drop by my poster tomorrow. ๐Ÿ—“๏ธ Tuesday, 8th of October 2024 ๐Ÿ•’ 10:30 - 11:30 AM ๐Ÿ–ผ๏ธ Self-supervised Vision Transformer are Scalable Generative Models for Domain Generalization [T-AM-233]
Another One!๐Ÿ“ข Excited to share that our paper "Self-supervised Vision Transformer are Scalable Generative Models for Domain Generalization" is accepted at #MICCAI2024! Want to know more? ๐Ÿ“: arxiv.org/abs/2407.02900 ๐Ÿ™: github.com/sdoerrich97/vits-โ€ฆ @MICCAI_Society @xAILabBamberg
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๐Ÿš€ Excited to introduce: "Unsupervised Feature Orthogonalization for Learning Distortion-Invariant Representations", wich will be presented as an oral at the #RROW Workshop at #BMVC2024 ๐Ÿด๓ ง๓ ข๓ ณ๓ ฃ๓ ด๓ ฟ. ๐Ÿ“: arxiv.org/abs/2409.12276 ๐Ÿ™: github.com/sdoerrich97/unoraโ€ฆ ๐Ÿ‘ฅ: @francescodis_, @LedigChr
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๐ŸŽบExcited to share yet another work of our #xAILabBamberg! This work, led by @francescodis_, is for all of you #ComputerVision folks out there interested in #privacy preserving and will be featured at this year's #BMVC conference in Glasgow, UK! ๐Ÿด๓ ง๓ ข๓ ณ๓ ฃ๓ ด๓ ฟ ๐Ÿ“: arxiv.org/abs/2408.00639

๐Ÿ“ฃ Our paper "Privacy-preserving datasets by capturing feature distributions with Conditional VAEs," has been accepted at #BMVC2024 ๐Ÿด๓ ง๓ ข๓ ณ๓ ฃ๓ ด๓ ฟ A huge thank you to all co-authors: David Tafler, @DoerrichS, and @LedigChr. Paper: arxiv.org/abs/2408.00639
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๐ŸŒŸ xAILAB Bamberg goes MICCAI - Part II ๐ŸŒŸ Another work from our group was accepted for #MICCAI2024! This work led by @francescodis_ will be presented at the Workshop on Advancing Data Solutions in Medical Imaging AI #ADSMI. ๐Ÿ“ arxiv.org/pdf/2406.17536 ๐Ÿ™ github.com/francescodisalvo0โ€ฆ

๐Ÿ“ฃ I am happy to share that our paper "MedMNIST-C: Comprehensive benchmark and improved classifier robustness by simulating realistic image corruptions" has been accepted to the #ADSMI workshop at #MICCAI2024! @MICCAI_Society @DaliWorkshop Paper: arxiv.org/pdf/2406.17536
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Another One!๐Ÿ“ข Excited to share that our paper "Self-supervised Vision Transformer are Scalable Generative Models for Domain Generalization" is accepted at #MICCAI2024! Want to know more? ๐Ÿ“: arxiv.org/abs/2407.02900 ๐Ÿ™: github.com/sdoerrich97/vits-โ€ฆ @MICCAI_Society @xAILabBamberg
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If you're at #ISBI2024 in #Athens right now, feel free to drop by our poster presentation tomorrow. ๐Ÿ—“๏ธDate: Tuesday, 28th of May 2024 ๐Ÿ“ Room: Banqueting Hall Foyer ๐Ÿ•’Time: 10:00 - 11:30 AM ๐Ÿ–ผ๏ธPoster: #980 See you there and if you want to know more, check out the post below!๐Ÿš€
๐Ÿš€Exciting news!๐Ÿš€ Our paper on "Integrating kNN with Foundation Models for Adaptable and Privacy-Aware Image Classification" has been accepted at #ISBI2024! Preprint๐Ÿ“: arxiv.org/abs/2402.12500 Code๐Ÿ™: github.com/TobArc/privacy-awโ€ฆ @xAILab
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๐Ÿ“Paper Alert!๐Ÿ“ Check out our latest research: "Rethinking Model Prototyping through the MedMNIST Dataset Collection" - the first baseline evaluation for the MedMNIST database. ๐Ÿ“: arxiv.org/abs/2404.15786 ๐Ÿ™: github.com/sdoerrich97/rethiโ€ฆ ๐Ÿ’พ: zenodo.org/records/10519652 @xAILabBamberg
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Big shoutout to Tobias for securing third place at the @_DMEA Newcomer Award!๐Ÿฅ‰ Please join us at the xAI Lab Bamberg in celebrating this remarkable achievement!๐Ÿ‘ Learn more: uni-bamberg.de/en/xai/news/aโ€ฆ Explore our research at xAI Lab Bamberg: uni-bamberg.de/en/ai/chair-oโ€ฆ @UniWiai
๐ŸŒŸ Celebrating the Next! ๐ŸŒŸ Tobias, one of my exceptional students, is a finalist for the prestigous "Newcomer Award" at @_DMEA 2024! Please join me in celebrating this outstanding achievement by voting for his contribution:๐Ÿ‘ youtube.com/watch?v=x45XKq3Qโ€ฆ @xAILab @UniWiai
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๐ŸŒŸ Celebrating the Next! ๐ŸŒŸ Tobias, one of my exceptional students, is a finalist for the prestigous "Newcomer Award" at @_DMEA 2024! Please join me in celebrating this outstanding achievement by voting for his contribution:๐Ÿ‘ youtube.com/watch?v=x45XKq3Qโ€ฆ @xAILab @UniWiai

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๐Ÿš€Exciting news!๐Ÿš€ Our paper on "Integrating kNN with Foundation Models for Adaptable and Privacy-Aware Image Classification" has been accepted at #ISBI2024! Preprint๐Ÿ“: arxiv.org/abs/2402.12500 Code๐Ÿ™: github.com/TobArc/privacy-awโ€ฆ @xAILab
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If you're around, feel free to drop by our poster presentation tomorrow at #MICCAI23. ๐Ÿ—“๏ธ Date: Sunday, 8th of October ๐Ÿ“ Room: Poster Hall, Ground Level Exhibition B-C ๐Ÿ•’ Time: 1:30 - 2:15 PM ๐Ÿ–ผ๏ธ Poster: P-7 Looking forward to sharing insights and discussions! See you there!๐Ÿš€
๐ŸŽ‰Excited to share our paper at #MICCAI23 #MLMI: "unORANIC", an unsupervised orthogonalization of anatomy and image characteristics. ๐Ÿ‘€No need for domain knowledge ๐Ÿ‘ŠImproved robustness against corruption Prep.: arxiv.org/abs/2308.15507 Source: github.com/sdoerrich97/unORAโ€ฆ @xAILab
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๐ŸŽ‰Excited to share our paper at #MICCAI23 #MLMI: "unORANIC", an unsupervised orthogonalization of anatomy and image characteristics. ๐Ÿ‘€No need for domain knowledge ๐Ÿ‘ŠImproved robustness against corruption Prep.: arxiv.org/abs/2308.15507 Source: github.com/sdoerrich97/unORAโ€ฆ @xAILab
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