> For the complete documentation index, see [llms.txt](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/special-applications/42-one-shotxue-xi-ff08-one-shot-learning.md).

# 4.2 One-Shot学习（One-shot learning）

[![](https://github.com/fengdu78/deeplearning_ai_books/raw/master/images/8b3b58571307fce29dbced077bd86ea7.png)](https://github.com/fengdu78/deeplearning_ai_books/blob/master/images/8b3b58571307fce29dbced077bd86ea7.png)

要让人脸识别能够做到一次学习，要做的是学习**Similarity**函数

让神经网络学习用$$d$$表示的函数：

$$
d(img1,img2) = degree\ of\ difference\ between\ images
$$

以两张图片作为输入，然后输出这两张图片的差异值

* 如果这两张图片的差异值小于某个阈值$$\tau$$，就能预测这两张图片是同一个人
* 如果差异值大于τ，就能预测这是不同的两个人

[![](https://github.com/fengdu78/deeplearning_ai_books/raw/master/images/f46e9ff3ef4819665b487a81784ab821.png)](https://github.com/fengdu78/deeplearning_ai_books/blob/master/images/f46e9ff3ef4819665b487a81784ab821.png)

对于人脸识别问题，只需计算测试图片与数据库中K个目标的相似函数，取其中d(img1,img2)最小的目标为匹配对象。若所有的d(img1,img2)都很大，则表示数据库没有这个人

如果之后有新人加入了团队（编号5），只需将他的照片加入数据库，系统依然能照常工作


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-si-men-ke-juan-ji-shen-jing-wang-luo-convolutional-neural-networks/convolutional-neural-networks/special-applications/42-one-shotxue-xi-ff08-one-shot-learning.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.