High performance body scanning technologies, powered by advanced imaging and deep learning, make high-definition security screening for on-person concealed objects under clothing available for secure facilities, data centers, airports, and sensitive manufacturing facilities. In this webinar, Rohde & Schwarz will present attendees with information on their R&S®QPS technologies, people screening systems and criteria for evaluating people screening technologies for specific security applications.

Attendees will learn:

1. How deep learning enables detection performance in a wide range of asset protection applications

2. Technical considerations when evaluating people screening/body scanning technologies, including:

o Concept of Operations

o Detection Requirements

o Versatility & Adaptability to new needs

o Safety & Privacy

o Reliability & Ease-of-use

3. Deployment and installation considerations when assessing body scanning technology

Credit Information

Completion of this webinar is eligible for 1 CPE credit. CPE credits for ASIS-sponsored webinars will be updated in your user profile within 48 hours of completion. Self-reporting of CPE credits is not required.

Presenter*

Christoph Baur

Director Software Imaging Products

Rohde & Schwarz GmbH & Co. KG

Germany

Christoph is the acting Director Software Imaging Products at Rohde & Schwarz Germany and leading the team responsible for all software-related activities concerning the Quick Personnel Scanner (QPS) line of body scanning systems from Rohde & Schwarz. His team brings together agile software development and cutting-edge machine learning research to turn millimetre-wave imaging technologies into high performance threat detection and asset protection devices.

Before he took over the responsibilities of the directing role a few months ago, Christoph was heavily involved in the development of the machine learning driven detection algorithms behind the QPS product line. With multiple years of academic machine learning research, numerous peer-reviewed scientific papers, roughly five years of hands-on experience with Deep Learning as well as close collaboration with customers and stakeholders in numerous projects, he understands both the opportunities and challenges involved – from both a technical and the business perspective. He is on the verge of finishing his PhD in Deep Learning & Artificial Intelligence and holds both a Master’s and Bachelor’s Degree in Informatics from Technical University of Munich. For more than 10 years, he has also been engaged in his own software-development company.

*Note: Speakers and content are subject to change without notice.