Neurala Collaborates with FLIR on AI-Powered Cameras

BOSTON, April 19, 2021 — Vision AI software provider Neurala is collaborating with FLIR Systems to develop a full software and hardware stack AI-based industrial imaging solution. The collaboration aims to build a faster and more cost-effective entry point for industrial imaging, smart camera development, and Industry 4.0 applications. The solution is able to create deep learning models and neural networks using Neurala’s Brain Builder on the VIA platform with little data and no AI expertise. The models can then be directly uploaded to a FLIR Firefly DL camera using FLIR’s application programming interface library.

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Published: April 2021

Glossary

machine vision: Machine vision, also known as computer vision or computer sight, refers to the technology that enables machines, typically computers, to interpret and understand visual information from the world, much like the human visual system. It involves the development and application of algorithms and systems that allow machines to acquire, process, analyze, and make decisions based on visual data. Key aspects of machine vision include: Image acquisition: Machine vision systems use various...
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...
neural network: A computing paradigm that attempts to process information in a manner similar to that of the brain; it differs from artificial intelligence in that it relies not on pre-programming but on the acquisition and evolution of interconnections between nodes. These computational models have shown extensive usage in applications that involve pattern recognition as well as machine learning as the interconnections between nodes continue to compute updated values from previous inputs.