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With each of the raw images at left (color), today's state-of-the-art
object-detection algorithms make errors that initially seem baffling — such as mistaking distant clouds for a nearby car. A new
technique enables the visualization of a common mathematical
representation of
images (in black and white), which should help researchers understand why
their
algorithms fail.

Teaching computers to see — by learning to see like computers

By translating images into the language spoken by object-recognition systems, then translating them back, researchers hope to explain the systems’ failures.

September 19, 2013