Fraunhofer Institute for Industrial Mathematics ITWM

Seminar

Deep Learning Seminar / May 20, 2021, 10:00 – 11:00

Adversarial Machine Learning in Computer Vision

Speaker: Peter Lorenz (Fraunhofer ITWM, Abteilung High Performance Computing)

Abstract:

In recent years, computer vision models have achieved increased performance on various recognition tasks. These models are vulnerable against adversarial examples. A small perturbation in the input image is enough for misclassification. Adversarial examples reveals that models perform differently with the human visual system, and provides opportunities for understanding and improving these models. Therefore, in this talk an overview of SOTA attacks and defenses will be given.

Event details

Program

Our speaker Peter Lorenz (Fraunhofer ITWM, Abteilung High Performance Computing) gives a lecture on the topic »Adversarial Machine Learning in Computer Vision«.

Contact

The seminar is held with the tool MS Teams. Click here on the meeting link. In order to use all functions, it is recommended to download the MS Teams App beforehand.

If you have any questions regarding the organisation, please contact Dominik Straßel (see contacts).

Location

The event takes place digitally.

Date

May 20, 2021, 10:00 – 11:00

Download this event as iCal

Language

English

About the Seminar Series

The Deep Learning Seminar is organized by employees of the field »Data Analysis and Machine Learning« in the department »High Performance Computing«. It is intended to give interested persons an insight into this large field of research and a deeper understanding. Everyone who wants to learn more about Deep Learning, Machine Learning or AI in general is invited - no matter if students, PhD students, professors or software developers. In addition to the employees of our department, interested external speakers can also give a lecture in our seminar series. We also have the opportunity to invite external speakers. We are always open to suggestions, suggestions or requests.

The event usually takes place every Thursday (except for holiday shifts and summer break). The topic of a talk should either come directly from or is relevant to Deep Learning, Machine Learning, Data Analysis or AI, no matter whether it is about a paper, an own project on or an interesting topic. The complexity can range from an overview talk to a special topic.