卷积神经网络 注意力机制_卷积神经网络中的注意

卷积神经网络 注意力机制

This summer I had the pleasure of attending the Brains, Minds, and Machines summer course at the Marine Biology Laboratory. While there, I saw cool research, met awesome scientists, and completed an independent project. In this blog post, I describe my project.

今年夏天，我很高兴参加了海洋生物学实验室的“ 大脑，思维和机器”暑期课程。 在那儿，我看到了很酷的研究，遇到了很棒的科学家，并完成了一个独立项目。 在这篇博客中，我描述了我的项目。

In 2012, Krizhevsky et al. released a convolutional neural network that completely blew away the field at the imagenet challenge. This model is called “Alexnet,” and 2012 marks the beginning of neural networks’ resurgence in the machine learning community.

在2012年，Krizhevsky等人。 发布了一个卷积神经网络 ，在imagenet挑战中完全消失了。 该模型称为“ Alexnet”，2012年标志着神经网络在机器学习社区中兴起的开始。

Alexnet’s domination was not only exciting for the machine learning community. It was also exciting for the visual neuroscience community whose descriptions of the visual system closely matched alexnet (e.g., HMAX). Jim DiCarlo gave an awesome talk at the summer course describing his research comparing the output of neurons in the visual system and the output of “neurons” in alexnet (you can find the article here).

Alexnet的统治不仅让机器学习社区兴奋不已。 对于视觉神经科学界来说，这也是令人兴奋的，他们对视觉系统的描述与alexnet（例如HMAX ）非常匹配。

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