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Prikvačeni tweet
We are happy to announce the
#NIPS2018#AdversarialVisionChallenge! It's designed to inspire progress towards more robust vision models & real-world attacks. Great to team up with@googleresearch,@crowd_ai and@pennstate & to have@awscloud as a sponsor! https://www.crowdai.org/challenges/nips-2018-adversarial-vision-challenge …pic.twitter.com/jzftu2kNMe
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Work together with Evgenia Rusak, Lukas Schott,
@zimmerrol, Julian Bitterwolf, Oliver Bringmann,@MatthiasBethge,@wielandbrPrikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Does your DNN have problems with common corruption robustness? You can get suprisingly far by just training on noise! In our new paper, we evaluate how simple learned i.i.d. noise can help to generalize to ImageNet-C. Blog post @ https://medium.com/bethgelab/increasing-the-robustness-of-dnns-against-image-corruptions-by-playing-the-game-of-noise-4566b5c2c8d5 …pic.twitter.com/sasN63kDyq
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Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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Bethge Lab proslijedio/la je TweetHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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Bethge Lab proslijedio/la je Tweet
Want to see how we bring interpretability to CNNs to predict V1 responses via end-to-end learning divisive normalization? Meet me at my poster W-56
#BernsteinConference With@SantiagoACadena@DenfieldGeorge@eywalker@AndreasTolias@MatthiasBethge@alxecker@bethgelab@AToliasLabHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Bethge Lab proslijedio/la je Tweet
#ccneuro2019: come check out our poster "The Notorious Difficulty of Comparing Human and Machine Perception" TOMORROW (Sunday, 17:15 - 20:15)!@cm_funke@wielandbr@bethgelab.Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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Bethge Lab proslijedio/la je Tweet
My
@bethgelab colleague @MaxGuenthner talking about modelling V1 with divisive normalization at#ccn19pic.twitter.com/zRYx0gvXx0
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Bethge Lab proslijedio/la je Tweet
the European Laboratory for Learning & Intelligent Systems (ELLIS) has now announced the 11 programs
#supportingELLIS :https://ellis.eu/en/news/ellis-programs-launched …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Bethge Lab proslijedio/la je Tweet
We will be presenting our study on the effectiveness of low frequency in generating adversarial perturbations
@IJCAIconf#IJCAI2019 at the Adversarial ML morning session!@BorealisAI https://arxiv.org/abs/1903.00073 pic.twitter.com/DDNbtdUpxz
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Happy to announce that our Robust Detection Benchmarking Toolkit is now part of the mmdetection toolbox! https://github.com/open-mmlab/mmdetection … Benchmark:https://github.com/bethgelab/robust-detection-benchmark …
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Can your object detector handle noise? What will your autonomous vehicle do when it's foggy? And more importantly: Is your D(rago)NN ready for Snow when Winter is Coming? Find out with our robust detection benchmark (Pascal, Coco & Cityscapes): https://arxiv.org/abs/1907.07484 pic.twitter.com/WaNcIcVV5p
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Bethge Lab proslijedio/la je Tweet
We developed gradient-based versions (L0, L1, L2 & Linf) of our Boundary adversarial attack that (1) resist gradient-masking, (2) perform better & are more query-efficient than SOTA (e.g. PGD or C&W) and (3) require virtually no hyperparameter tuning: https://arxiv.org/abs/1907.01003
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Bethge Lab proslijedio/la je Tweet
Gradient descent will take any shortcut available to map inputs to targets. Human perception works differently: it starts from a different input (embodied stream vs static images), it doesn't have a target for each input, and it isn't trained with SGD.https://www.quantamagazine.org/where-we-see-shapes-ai-sees-textures-20190701/ …
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Article discussing our recent work investigating the properties of current state-of-the-art algorithms. Hope to see more in this line of research!https://www.quantamagazine.org/where-we-see-shapes-ai-sees-textures-20190701/ …
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Bethge Lab proslijedio/la je Tweet
And now, #DeepLabCut 2.0 is published! https://rdcu.be/bHpHN@NatureProtocols 3D Markerless pose estimation of user-defined points across any species.#FreeSoftware#OpenSource Full step-by-step guide,@GoogleColab Notebooks, & more!
co-1st: @TrackingPlumes &@meet10maypic.twitter.com/4f1ndll55OPrikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Bethge Lab proslijedio/la je Tweet
Hey tweeps. This week I started a new position as a research scientist at Amazon! I will miss all my colleagues from the
@bethgelab, where I've learned so much. Now, I'm excited to apply vision science at Amazon scale!Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Bethge Lab proslijedio/la je Tweet
We just updated our "One-Shot Instance Segmentation" paper https://arxiv.org/abs/1811.11507 and code https://github.com/bethgelab/siamese-mask-rcnn … …! Now featuring additional few-shot results, a more robust way to evaluate and a lot of other improvements!
@ivust@alxecker@MatthiasBethge@bethgelabpic.twitter.com/ePcjoVvLzw
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Bethge Lab proslijedio/la je Tweet
Our paper is finally out!! With available data (https://doid.gin.g-node.org/2e31e304e03d6357c98ac735a1fe5788/ …) and code: (https://github.com/sacadena/Cadena2019PlosCB …) Work with
@ScrawnyG@eywalker Leon Gatys@bethgelab@AToliasLab and@alxeckerhttps://twitter.com/PLOSCompBiol/status/1124028280774905857 …
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Today is our big day
@iclr2019. Checkout Roberts oral on shape vs texture at 4pm. We also have several posters on robustness, interpretability and neuroscience: AM posters: #34 and #49 PM posters: #65, #69 and #78 Looking forward to seeing youHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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