AI video analysis software improves face classification accuracy

AI video analysis software improves face classification accuracy

New Products |
BrainChip has updated its Studio video analysis software to version 2018.3. The new update includes a mode to improve face classification accuracy by 10-30 percent.
By Rich Pell


BrainChip Studio traditionally used spiking neural networks to enable facial classification on partial faces. This partial-face mode is useful in situations where the probe image or the extracted faces may be obscured due to hats, masks, scarves or camera angle.

BrainChip Studio 2018.3 uses a full-face mode to perform facial classifications. In situations where the entire face is visible in the probe image or in the extracted faces, this new mode provides a significant increase in facial classification accuracy. Depending on the dataset used, testing indicates this mode provides a 10-30 percent improvement in accuracy, without impacting throughput.

“We are always looking for ways to continually improve our products by listening to our customer requests,” said Bob Beachler, BrainChip’s Senior Vice President of Marketing and Business Development. “Improving accuracy is typically at the top of list for video analytic software. With BrainChip Studio 2018.3 we were able to provide a dramatic increase in accuracy.”

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