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Low-level computer vision algorithms have high computational requirements.
The team, part of the Computational Vision and Geometry Lab, has already been working on computer vision algorithms that track and aim to predict pedestrian movements.
Distributed computer vision algorithms require careful design.
Epipolar geometry estimation is fundamental to many computer vision algorithms.
For computer vision algorithms, it's difficult to reconcile the two different versions of a shirt.
Planar geometric curve evolution equations are the basis for many image processing and computer vision algorithms.
A large corpus of images is needed to train computer vision algorithms to distinguish between cats, dogs, and houseplants.
Deep convolutional neural networks (CNNs) are indispensable to state-of-the-art computer vision algorithms.
However, with advances in computer vision algorithms bots are increasingly successful in passing these tests.
Many computer vision algorithms rely on precise estimates of scene radiances obtained from an image.
Computer vision algorithms running on these camera boards should be light-weight and efficient.
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