Case Study: FLIR achieves market-leading thermal AI capabilities with CVEDIA synthetic data

Using synthetic technology to service new generation smart thermal cameras

FLIR, the global leader in thermal cameras, needed a way to support its AI roadmap but struggled to gather enough training data for computer vision use cases. The company found that collecting enough real-world thermal images was too expensive and time-consuming, especially across commercial, defense, and automotive applications. CVEDIA helped address this challenge with synthetic data technology for thermal neural network training.

Working as a partner with FLIR, CVEDIA built and integrated a synthetic thermal data pipeline into FLIR’s engineering workflow, enabling training for multiple use cases without additional real-world data collection. The solution helped FLIR develop autonomous capabilities, support applications from aerial and maritime to animal detection, and launch CVEDIA-powered deer collision prevention and defense systems such as AiTR and troop protection.

FLIR

Pierre Boulanger

Chief Technology Officer