CEVA Software Framework Brings Deep Learning to Embedded Vision Systems

CEVA Software Framework Brings Deep Learning to Embedded Vision Systems Inside DSP – BDTiOct. 22, 2015 As Jeff Bier has mentioned in several of his recent columns, deep learning algorithms have gained prominence in computer vision and other fields where there’s a need to extract insights from ambiguous data. Convolutional neural networks (CNNs) – massively parallel algorithms made up of layers of computation nodes – have shown particularly impressive results on challenging problems that thwart traditional feature-based techniques; when attempting to identify non-uniform objects, for example, or in sub-optimal viewing conditions. However, as with many emerging technologies, much of the R&D work on CNNs is being undertaken on resource-rich PC platforms. CEVA’s just-introduced Deep Neural Network (CDNN) software framework aspires to optimize CNN code and data for more modestly equipped…


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