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- W2587166551 abstract "Deep learning is currently the state of the art algorithm for image classification. The complexity of these feedforward neural networks have overcome a critical point, resulting algorithmic breakthroughs in various fields. On the other hand their complexity makes them executable in tasks, where High-throughput computing powers are available. The optimization of these networks -considering computational complexity and applicability on embedded systems- has not yet been studied and investigated in details. In this paper I show some examples how this algorithms can be optimized and accelerated on embedded systems." @default.
- W2587166551 created "2017-02-17" @default.
- W2587166551 creator A5070051531 @default.
- W2587166551 date "2017-02-08" @default.
- W2587166551 modified "2023-09-23" @default.
- W2587166551 title "Optimization of deep learning algorithms for object classification" @default.
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- W2587166551 doi "https://doi.org/10.1117/12.2266403" @default.
- W2587166551 hasPublicationYear "2017" @default.
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