‘Artificial Intelligence’ at EMVA Virtual Business Conference

Jürgen Beyerer and Bruno Maisonnier will be presenting at EMVA Virtual Business Conference 2020

Be prepared for an exciting programme of the first EMVA Virtual Business Conference, June 26th, 2020. Presentations from leaders and innovators in our industry will present relevant topics such as 3D Vision, Autonomous Navigation, Deep Learning, Photonics and more.

EMVA is pleased to present two top speakers who will address

‘Artificial Intelligence’ in the context of Qualty Control and Inspection.

‘Machine Learning and Artificial Intelligence for Automated Visual Inspection’

Dr. Ing. Jürgen Beyerer is a full professor for informatics at the Institute for Anthropomatics and Robotics at the Karlsruhe Institute of Technology (KIT) since March 2004 and director of the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation (IOSB) in Ettlingen, Karlsruhe, Ilmenau, Lemgo, and Görlitz. He is Spokesman of the Fraunhofer Group for Defense and Security VVS and he is member of acatech, National Academy of Science and Engineering. Furthermore, he is Head of team 7 of the platform „Lernende Systeme“ and Spokesman of the Competence Center Robotic Systems for Decontamination in Hazardous Environments (ROBDEKON).

Research interests include automated visual inspection, signal and image processing, pattern recognition, metrology, information theory, machine learning, security, system theory, autonomous systems and automation.

Abstract of Jürgen Beyerer´s presentation:

In his presentation Jürgen Beyerer will address, how ML approaches can be used in Automated Visual Inspection (AVI). Questions that will be discussed are inter alia: What are the potentials of ML-methods in AVI? How can sufficiently enough data be amassed necessary for deep learning? How can data be augmented synthetically? How can prior knowledge be exploited in order to cope with little data? How can AI-approaches help to design complex AVI-systems?

‘Artificial Intelligence Learning at the Edge — Application to Integration-Free Quality Control’

French serial entrepreneur and innovator, Bruno Maisonnier is founder and CEO of AnotherBrain, world category leader in 3rd generation AI, and the Founder & ex-CEO of Aldebaran Robotics.

Passionate about technology and the way it can improve people’s everyday lives, in 2017, Bruno founded AnotherBrain, startup which brings Organic AITM, a new generation of artificial intelligence which is bio-inspired, explainable and self-learning. In 2005, Bruno developed from scratch Aldebaran Robotics, which became the world leader in humanoid robotics. Sold to a Japanese giant in 2015, the company became SoftBank Robotics.

Abstract of Bruno Maisonnier´s presentation:

Today the mainstream of Artificial Intelligence (AI) is based on fully supervised deep neural networks. Mainly used on classification tasks, they brought a major disruption in terms of performance with respect to traditional rules-based computer vision solutions. Nevertheless, because of the complexity of data gathering and supervision, they still require specialists, i.e. data scientists to train the solution offline and only inference is applied on the edge. As a result, most of current AI solutions fail to deliver the promise of artificial intelligence, i.e. a system that is able to be trained and operated directly by the end user. While this may still be a good answer to issues involving generic data like cars or pedestrians for which huge datasets exist on the cloud, AnotherBrain believes that applications where data is very scarce and specific to the customer require a new approach, a third generation of Artificial Intelligence.

This talk is dedicated to the review of this solution and its technical contributions to the field of automatic quality control.

Don’t miss the outstanding opportunity to join the 18th edition of EMVA’s Business Conference and click the below for all details.

* Income from registration fees will be donated to the COVID-19 Solidarity Response Fund, led by the WHO

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