Pleora and Lemay.ai Partner on Real-Time Imaging Applications

OTTAWA, Ontario, Aug. 19, 2019 — Pleora Technologies and Lemay.ai have partnered to integrate machine learning into real-time imaging applications. Lemay.ai’s artificial intelligence expertise will be integrated directly into Pleora’s smart frame grabber and embedded interface products. The technology will also be available as a configurable stand-alone software development kit for real-time vision applications.

The companies are also collaborating on smart imaging products that integrate real-time sensor networking and machine-learning-based object detection, tracking, and classification for industrial automation systems.

“AI promises to significantly improve decision making and automation across all markets served by real-time imaging, but designers are struggling with the cost and complexity of implementation,” said Harry Page, president of Pleora Technologies. “Partnering with Lemay, we’re significantly lowering the barrier to entry so designers and end users can quickly and cost-effectively leverage the benefits of AI, machine learning, and sensor networking through drop-in hardware and software solutions.”

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Published: August 2019

Glossary

machine learning: Machine learning (ML) is a subset of artificial intelligence (AI) that focuses on the development of algorithms and statistical models that enable computers to improve their performance on a specific task through experience or training. Instead of being explicitly programmed to perform a task, a machine learning system learns from data and examples. The primary goal of machine learning is to develop models that can generalize patterns from data and make predictions or decisions without being...
embedded vision: Embedded vision refers to the integration of computer vision technologies into various embedded systems, devices, or machines. Computer vision involves teaching machines to interpret and understand visual information from the world, much like human vision. Embedded vision takes this concept and applies it to systems where the processing occurs locally within the device, as opposed to relying on external servers or cloud-based services. Key components of embedded vision systems include: ...

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