Thursday, June 17, 2021
9:30 AM - 10:00 AM (EDT)

Industry-leading vision systems from Matrox Imaging are engineered to deliver exceptional performance in harsh industrial environments. Their latest edge IoT device—the Matrox Iris GTX smart camera—is a powerful, compact all-in-one vision system. Driven by flowchart-based software and powered by the latest Intel Atom embedded processor, these new systems adeptly handle traditional machine vision workloads as well as deep learning inference. Matrox Iris GTX  capably perform on-device image acquisition and processing for real-time, optimized response and action. This discussion will explore the latest technical innovation from Matrox Imaging, including deep learning and other capabilities and features. 

Fabio Perelli Chris Mc loone

10:00 AM - 10:15 AM (EDT)

Although thermal imaging with infrared cameras has a great potential especially in industrial applications, it has only made its way into automation and quality assurance to a very limited extend. While with the introduction of uncooled detectors the essential base technology for the design of thermal industrial cameras is available now for more than 20 years, many obstacles still remain. One important reason for the low spread in industry is the lack of standard software for thermal imaging. Integrators have to use SDK’s provided by the camera manufacturers to develop their own software solutions which means a high hurdle. Furthermore, the camera models available today are not consistently designed for industrial applications. Manufacturers have a lack of application experience and they still don‘t see industry as a relevant target market. To mention a third point, the acceptance of computer-based imaging systems tends to decline. Among others, some reasons are the complexity of such systems, costs, stability, data safety and maintenance effort.
The lecture presents a new device-related approach with smart thermal cameras to address the obstacles for practical applications and to make the potential of temperature imaging in industrial environments accessible.

Guido Deutz

10:15 AM - 10:30 AM (EDT)

Achieving real-time decision making and predictive analytics is an increasingly strategic goal among industrial operations – an imperative fueled by rapid digital transformation and a growing appetite for automation upgrades across the broad spectrum of commercial and manufacturing applications. Rugged edge computing plays a critical role in this landscape, accelerating data processing based on a variety of sensor input data and enabling access and analytics close to the data source. For example, the primary goal of many new IoT applications is the delivery of a level of intelligence refined beyond human capabilities or pace. In these applications, machine learning is required but must be supported by dedicated hardware to process and run algorithms effectively. 

At the same time, engineers are often forced to design compute solutions for scenarios where they lack experience to meet these growing IoT demands. Rugged edge computers address such challenges and are specifically developed to withstand the rigors of harsh usage conditions with built-in durability and ruggedized features throughout. Premio’s heritage in rugged edge computing solutions fills the void. It uniquely positions industrial leaders to effectively balance the performance, reliability, footprint, and longevity requirements of new and more sophisticated industrial IoT deployments. 

As our digital world continues to shift and transform enterprise business landscapes into smarter digital atmospheres, the best computing solutions act on data insights for real-time processing and deliver intelligent results. Especially with faster, power-efficient cores jampacked into smaller nanometer silicon for blazing fast compute power and 5G wireless connectivity on the horizon, the next generation of embedded IoT solutions will consolidate the most complex workloads and enable machine learning for a future of artificial intelligence. 

Dustin Seetoo

10:30 AM - 11:00 AM (EDT)

This webinar focuses on the basics of 3D vision technology. In the discussion, you’ll learn about: 
•    New advancements in 3D technology
•    Types of 3D vision systems and how they are used in factory automation
•    Several inspection and application examples across industries

Isabel Pagliccio

11:00 AM - 11:15 AM (EDT)

This webinar will illustrate how relying on Sensor to Image FPGA IP Cores will ease and accelerate the design, implementation and deployment of your next camera or embedded vision system.

Michael Cyros

11:15 AM - 11:30 AM (EDT)

3D localization technologies provide flexibility and robustness for a vast number of robotics applications, e.g. machine tending, pick-and-place applications, and the referencing of AGV. 

The brand new Target Mark 3D technology is SensoPart’s latest approach in providing an easy-to-use 3D localization solution, combining platform independence with highly accurate 3D pose information. 

Starting out by defining what sets Target Mark 3D apart from it’s competitors technologies, SensoPart’s Alexander Resch will be discussing the technologies origins, appropriate industrial fields and applications, and the key benefits a business can expect from deploying Target Mark 3D.

Alexander Resch

11:30 AM - 12:00 PM (EDT)

If your robot can see more, it can do more! But, how do you reap the benefits of mounting your 3D camera on the robot arm? What are the enabling technology and key considerations you need to take when moving from traditional stationary mounted depth sensing to fast, on-arm 3D vision?

Attaching your industrial 3D camera directly to the robot arm gives you incredible flexibility, maneuverability, and image quality. In this session, you'll learn about the benefits AND the challenges and see examples of the award-winning industrial 3D color cameras from Zivid.

The session is suitable for everyone looking for inspiration, how to get started, or potentially afraid to step into the ultimate challenge in 3D-vision-based robotics.

Alex Koepsel

12:00 PM - 12:30 PM (EDT)

Powerful embedded vision creates added value and new possibilities for many industrial products. Jan-Erik Schmitt from Vision Components demonstrates multiple ways to integrate camera technology in hardware designs. He shares the company's know-how and experience, from the invention of the first industrial-grade intelligent camera 25 years ago to state-of-the-art MIPI Camera Modules, Board-level cameras and ready-to-use solutions.

Jan-Erik Schmitt

12:30 PM - 1:00 PM (EDT)

The reality for most manufacturers? AI machine vision deployments can be challenging. Getting it right takes determination and dedication to optimizing the process. Landing AI's Quinn Killough will discuss what barriers are preventing AI from getting to production, and how manufacturers can move past the obstacles. 

Quinn Killough

1:00 PM - 1:15 PM (EDT)
Ray Berst

1:15 PM - 1:30 PM (EDT)

Donal will talk about the introduction if the xB series, which replaces the highly populat Neon family and how he sees the future of Camera Link in industry.

Donal Waide

1:30 PM - 2:00 PM (EDT)

- What kind of applications are well suited for embedded systems
- Key performance parameters for embedded systems 
- A review of the accessory ecosystem including a comparison of ARM boards
- Considerations when working with board level cameras  

William Gallego

2:00 PM - 2:30 PM (EDT)

After a brief introduction of Bin Picking and its challenges for computer vision, Matthew Breit will explain the benefits of the Time-of-Flight technology for bin picking tasks. This session will also show you how 3D vision middleware can help to integrate the ToF camera into your robot bin picking system. 

Matthew Breit

2:30 PM - 3:00 PM (EDT)

Deep learning has undoubtedly opened up many areas of industry that had been previously inaccessible for traditional machine vision. There is no longer a need to spend weeks on creating rule-based algorithms for quality inspection and eventually end up having to completely re-design them due to slight changes in the object shape or structure. Not to mention tasks that were simply not feasible in the past, whereas now, using tools for feature and anomaly detection, we can approach them and move ahead of our competitors.  

It turns out, however, that deep learning-based tools more and more often end up complementing traditional machine vision and the best results are achieved when we put them together. 

In this webinar, you will learn how to combine deep learning with traditional machine vision algorithms using real-life projects as an example.

Mateusz Barteczko

3:00 PM - 3:15 PM (EDT)

PCIe and Multicamera setups
Embedded Camera Systems with the highest bandwidth
Quick chat with Kevin Toerne, Sales Engineer at XIMEA

Kevin Toerne

3:15 PM - 3:45 PM (EDT)

Mission-critical applications such as those in artificial intelligence, machine vision, robotics, surveillance, and autonomous vehicles demand reliable PCs that can withstand harsh environments that ordinary PCs cannot. Industrial PC customers needs scalability, longevity, and repeatability. In this QuickChat interview, CoastIPC president John DeWaal will discuss the value that CoastIPC brings to the industrial automation marketplace. You’ll also hear from Skye Gorter, President of machine vision systems integration company Skye Automation, who will talk about the difference that CoastIPC brings to his company’s systems, which are deployed in more than 20 countries around the globe.  

John DeWaal Skye Gorter Chris Mc loone

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