Name: [PDG 146] Approximating CNNs with Bag-of-local-Features models
Start: 2019-05-02T18:30:00+02:00
End: 2019-05-02T20:30:00+02:00
Location: Informatik-Gebäude des KIT (50.34) Raum -120

Machine Learning Paper Discussion Group

In the Paper Discussion Group (PDG) we discuss on a weekly base recent and fundamental papers in the area of machine learning. For several weeks, we follow one track to dive a bit deeper into a topic by reading matching or correlate papers. If you are interested, read the paper and join us.

Track: Open
Topic: Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet
Paper: https://arxiv.org/abs/1904.00760

Jörg Franke

karlsruhe.ai

Technology

Data Analytics

Neural Networks

Artificial Intelligence Applications

Artificial Intelligence

Professional Development

New Technology

Knowledge Sharing

Big Data

Machine Learning

Predictive Analytics

Machine Intelligence

Applied Statistics

Deep Learning

Timo Denk

Marcel Köpke

Hans-Peter Zorn

Patrick Wiener

Jan Löffler

Muhammad Ali Zia

Amir

[PDG 146] Approximating CNNs with Bag-of-local-Features models

Informatik-Gebäude des KIT (50.34) Raum -120

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karlsruhe.ai

[PDG 146] Approximating CNNs with Bag-of-local-Features models

karlsruhe.ai

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