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Researchers Make Progress Toward Computer Video Recognition

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Google researchers are working to advance video-recognition technology, which Rajat Monga on Google's Brain team says is due to progress in deep-learning models. "With the sequence of frames in each video that are related to each other, it provides a much richer perspective of the real world, allowing the models to create a [three-dimensional] view of the world, without necessarily needing stereo vision," Monga says. He concedes true human-like vision using video recognition is "still far away" because computers can only recognize some, but not all, objects in images. Computers need to be educated to recognize images in deep-learning models, and big datasets can be used to cross-reference items in pictures.

Monga says Google researchers currently are studying how deep learning could help robots with hand-eye coordination and learning via predictive video. But he notes although deep learning is improving thanks to faster computing, algorithms, and datasets, more progress is required.

Monga says the emergence of faster hardware and custom chips such as Google's machine-learning Tensor Processing Unit have helped advance deep learning. Low-level calculations on graphical-processing units are fueling most deep learning models today, but faster hardware is expected to accelerate learning and deduction.

From IDG News Service 
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