Real-Time Sensor Networking and Machine Learning for Military Imaging
This webinar hosted by Pleora provides an overview on the role for real-time sensor networking and AI in military imaging systems, including driver enhancement and local situational awareness C4ISR applications.
The webinar covers:
- How new technologies support end-user requirements to increase awareness and reduce cognitive burden
- Designing next-generation distributed, networked “C4ISR.ai” systems
- Sensor & machine learning technologies for advanced decision-support
- Leveraging AI to support decisions
“I need AI! What is AI?”
Artificial intelligence is undoubtedly one of the most hyped technologies of recent times, and with market hype comes a lot of confusion. And it’s OK to be confused – Pleora designs artificial intelligence solutions, and we’re learning every day about new machine learning techniques and capabilities. Luckily, at Pleora we have the benefit of learning from a leading expert in the field of AI for machine learning.
Join Wassim El Ahmar, an artificial intelligence engineer at Pleora, for a free webinar on the ABCs of AI. In 30 minutes Wassim will help you:
About your host: Wassim El Ahmar has extensive expertise in AI and deep learning, including researching, developing, optimizing, and deploying AI systems for automated machine vision applications and embedded systems. Wassim is a PhD Candidate at the University of Ottawa, conducting research on deep learning optimization for embedded systems and auto machine learning, and is a part-time professor at the School of Electrical Engineering and Computer Science.
Deploying Hybrid AI to Reduce Inspection Costs
Think AI is too costly or complex? Watch this on-demand webinar hosted by Pleora Technologies for practical insight on using “hybrid AI” to add advanced capabilities alongside existing inspection systems and processes to improve results and reduce costs.
This on-demand webinar covers:
- What is “hybrid AI” and how does it support the addition of advanced machine learning capabilities to reduce costs and complexity?
- How will AI influence future manufacturing processes?
- A case study on one leading manufacturer now adopting hybrid AI in retrofit and secondary screening systems.