Deep learning for vision processing: The emerging algorithm alternative

As the recent 4-to-1 drubbing of Go world champion Lee Sedol by Google’s DeepMind AlphaGo program signifies, artificial intelligence has entered mainstream awareness. It’s enabled by the evolution of traditional neural network approaches, the steadily increasing processing acceleration “muscle” of FPGAs, GPUs and dedicated co-processors, and the steadily decreasing cost of system memory. Among the most compelling uses for so-called “deep learning” techniques such as convolutional neural networks is object identification in images, where the approach offers compelling advantages over conventional computer vision algorithms. [Native Advertisement] Traditional rule-based object recognition algorithms require the mathematical modeling and algorithmic coding of a software function capable of reliably identifying a particular object within a still image or video frame. Unfortunately, even if such an approach can be made reasonably reliable under some conditions,…

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