Chetan Khona, Director Industrial, Vision, Healthcare & Sciences | AMD Chetan Khona is the Director of Industrial, Vision, Healthcare & Sciences markets at AMD, based in New York. Before joining AMD in February 2022, Chetan was captivated by the creative potential of Xilinx devices to solve embedded design challenges in a fundamentally differentiated and efficient manner while a student at the Georgia Institute of Technology. Chetan has continuously been involved with Xilinx now AMD as either a customer, engineer, salesperson, or marketer for over 25 years. These days, Chetan’s efforts have been focused on driving AMD roadmap and strategies to address the rise of AI and other embedded processing technologies at the IIoT edge supporting intelligent and adaptive factories, hospitals, and infrastructure applications. Chetan holds a Computer Engineering degree from Georgia Tech and a MBA from the University of Rochester.
Julien Bernet Julien is a vulnerability research engineer. After a PhD in theoretical computer science, he’s been working for various security labs with a focus on software security for embedded devices and smart cards. He’s been involved in many security evaluations and has a soft spot for the use of formal methods in software security. He is now Security Manager at Witekio, in charge of the development of the internal security framework and defining the security architecture for developments.
Mario Bergeron Mario Bergeron is a Technical Marketing Engineer for Avnet, specializing in embedded vision and machine learning. Mario has a Bachelor of Science degree in Computer Engineering from Université Laval in Québec City. He started his career as an ASIC designer and has since then accumulated over 30 years of DSP and FPGA based embedded design experience. Present activities include deep learning platforms, reference designs, and customer training.

Software and Cybersecurity Challenges for Robust Smart Camera Applications Solved with AMD-Xilinx Kria SOMs

In partnership with Avnet

With vision systems rapidly evolving to keep up with the demands of increasingly complex applications, total system performance and security are some of the top concerns. AMD-Xilinx is addressing these concerns with their Kria SOMs which acquire and preprocess video, run inference and stream results with an integrated GStreamer pipeline without HDL coding. All of this is done while maintaining all security requirements.

Join our experts who will present a tutorial based on AMD-Xilinx Kria SOM that explains how to setup robust vision systems with Machine Learning (ML) and implement the appropriate security requirements and best practices to develop secured software and ML on SOMs.

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