May 2020
Intermediate to advanced
530 pages
17h 8m
English
Content preview from Hands-On Machine Learning with C++
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Convolution network architecture
The network is developed from a small number of low-level filters in the initial stages to a vast number of filters, each of which finds a specific high-level attribute. The transition from level to level provides a hierarchy of pattern recognition.
One of the first convolutional network architectures that was successfully applied to the pattern recognition task was the LeNet-5, which was developed by Yann LeCun, Leon Bottou, Yosuha Bengio, and Patrick Haffner. It was used to recognize handwritten and printed numbers in the 1990s. The following diagram shows this architecture:
The network layers of this architecture ...
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