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The paper points out that the traditional convolution operation is actually a kind of cross-correlation operation used to measure the similarity between input features and convolution kernels, and this cross-correlation operation introduces many multiplication operations which increase the computation cost and energy consumption, so the paper proposes another way to measure the similarity between input features and convolution kernels, which is $\ell_1$ distance.

This article will try to explain the architecture of Faster R-CNN from the perspective of implementation. As Fast R-CNN has a complex process and many symbols, it is easy to be confused. Thus, here vgg16 is taken as an example, and all illustrations and variables are based on VGG-16 + VOC2007.

1 The Origin of CNN The study of artificial intelligence may be traced back to the ancient Greeks Aristotle who proposed Associationism theory in order to explain the operation of the human brain, he probably would not have thought that nowadays, more than 2000 years later, people are using the artificial neural network derived from associationism to build super artificial intelligence.

To maximize the advantages of containers, NVIDIA developed a software eco-system for containers as shown in the above figure, and published a registry of NGC containers. This document will introduce the concepts of NGC, set up a machine learning development environment using NGC containers, and implement a typical application scenario.

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