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Note: this content has been automatically generated.
00:00:01
uh_huh
00:00:04
nice place and i work on detecting unusual obstacles
00:00:09
in traffic images in order to improve the safety of
00:00:12
set of driving cars uh let's say our car 'cause it come or how does it know what it sees
00:00:19
common approach is to assign label every peak so the pet pixels belong to
00:00:24
the route between once the trees and the dark it was to the cox
00:00:29
this is called semantic segmentation it is often done made you run networks
00:00:35
they are very you they work very well but
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they require many traded examples thousands of images don't labels
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we had those examples for common classes such as people cars buildings rolls
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and so on however when we encounter red objects such as an aimless
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or last cargo which the network is never seen training
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it fails to notice the objects or produces nonsense outputs
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i want to take these cases and usually working the ten unknown objects press it's
00:01:11
my approach is to reconstruct the image from the labels
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then i found find how it differs from the original image
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if an object is incorrectly they but it will not look to send reconstruction
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these differences show us what the labels are wrong
00:01:31
here is an example we some laws boxes i hope this work will improve the safety of sort
00:01:36
of driving cars as well as the tact interesting training cases for other are great it's thank you

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Conference Program

Welcome address
Martin Vetterli, President of EPFL
June 6, 2019 · 9:48 a.m.
1565 views
Introduction
James Larus, Dean of IC School, EPFL
June 6, 2019 · 9:58 a.m.
127 views
Introduction
Jean-Pierre Hubaux, IC Research Day co-chair
June 6, 2019 · 10:07 a.m.
227 views
Adventures in electronic voting research
Dan Wallach, Professor at Rice University, Houston, USA
June 6, 2019 · 10:14 a.m.
When foes are friends: adversarial examples as protective technologies
Carmela Troncoso, Assistant Professor at EPFL
June 6, 2019 · 11:09 a.m.
169 views
Low-Latency Metadata Protection for Organizational Networks
Ludovic Barman, LCA1|DeDiS, EPFL
June 6, 2019 · noon
148 views
Interactive comparison-based search, and who-is-th.at
Daniyar Chumbalov, INDY 1, EPFL
June 6, 2019 · 12:06 p.m.
137 views
Decentralized, Secure and Verifiable Data Sharing
David Froelicher, LCA1|DeDiS, EPFL
June 6, 2019 · 12:09 p.m.
102 views
Communication Efficient Decentralised Machine Learning
Anastasia Koloskova, MLO, EPFL
June 6, 2019 · 12:11 p.m.
734 views
Detecting the Unexpected via Image Resynthesis
Krzysztof Lis, CVLab, EPFL
June 6, 2019 · 12:14 p.m.
188 views
Sublinear Algorithms for Graph Processing
Aida Mousavifar, THL4, EPFL
June 6, 2019 · 12:16 p.m.
880 views
Protecting the Metadata of Your Secret Messages
Kirill Nikitin, DEDIS, EPFL
June 6, 2019 · 12:18 p.m.
343 views
Teaching a machine learning algorithm faster
Farnood Salehi, INDY 2, EPFL
June 6, 2019 · 12:21 p.m.
570 views
Secure Microarchitectural Design
Atri Bhattacharyya, PARSA/HexHive, EPFL
June 6, 2019 · 12:23 p.m.
3489 views
Security testing hard to reach code
Mathias Payer, Assistant Professor at EPFL
June 6, 2019 · 1:50 p.m.
297 views
Best Research Presentation Award Ceremony
Bryan Ford, Jean-Pierre Hubaux, Deirdre Rochat, EPFL
June 6, 2019 · 3:54 p.m.
212 views

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