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Deep Vision Becomes Reality with CNN

Neural networks execute complex image processing tasks
Deep learning with neural networks will strongly influence the future of image processing, as this approach
provides a number of significant advantages regarding classification and analysis results as
well as final image quality. Since small neural networks suffice for many typical vision applications,
processors such as FPGAs can be implemented effectively for convolutional neural networks (CNNs).
This results in a wide application field far beyond current classification tasks and efficient use within
embedded vision systems is also possible.

Bayer interpolation on a GPU

Most of today’s color image sensors, use the Bayer filter mosaic, an array
of RGB color filters arranged on a grid of photosensors.
Named after the late Bryce Bayer (1929–2012) who invented it while working
for Eastman Kodak(Rochester, NY; USA),
the filter uses twice as many green elements to mimic the physiology of the
human eye.

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