English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Conference Paper

FrequencyLowCut Pooling - Plug & Play against Catastrophic Overfitting

MPS-Authors
/persons/resource/persons251916

Jung,  Steffen
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society;

/persons/resource/persons180612

Keuper,  Margret
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society;

External Resource
No external resources are shared
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)

2204.00491.pdf
(Preprint), 2MB

Supplementary Material (public)
There is no public supplementary material available
Citation

Grabinski, J., Jung, S., Keuper, J., & Keuper, M. (2022). FrequencyLowCut Pooling - Plug & Play against Catastrophic Overfitting. In S. Avidan, G. Brostow, M. Cissé, G. Farinella, & T. Hassner (Eds.), Computer Vision -- ECCV 2022 (pp. 36-57). Berlin: Springer. doi:10.1007/978-3-031-19781-9_3.


Cite as: https://hdl.handle.net/21.11116/0000-000A-C016-4
Abstract
There is no abstract available