right component when offering them help fixing their wireless net‐
work, or providing informative overlays on top of landscape fea‐
tures. Embedded applications often need to count objects that are
passing by, whether it’s pests in a field of crops or people, cars, and
bikes going past a street lamp.
TensorFlow offers a pretrained model for drawing bounding boxes
around people detected in images, together with tracking code to
follow them over time. The tracking is especially important for
applications in which you’re trying to count how many objects are
present over time, since it gives you a good idea when a new object
enters or leaves the scene, such as in this Android example.
Gesture recognition
It can be very useful to be able to control applications with hand or
other gestures, either recognized from images or through analyzing
accelerometer sensor data. Creating those models is beyond the
scope of this guide, but TensorFlow is an effective way of deploying
them.
Optical character recognition
There are multiple steps involved in recognizing text in images. You
first have to identify the areas where the text is present, which is a
variation on the object localization problem, and can be solved with
similar techniques. Once you have an area of text, you interpret it as
letters and then use a language model to help guess what words
those letters represent. The simplest way to estimate what letters are
present is to segment the line of text into individual letters, and
apply a simple neural network to the bounding box of each one.
You can get good results with the kind of models used for MNIST,
which you can find in TensorFlow’s tutorials, although you may
want a higher-resolution input.
A more advanced alternative is to use an LSTM model to process a
whole line of text at once, with the model itself handling the seg‐
mentation into different characters.
Translation
Translating from one language to another quickly and accurately,
even if you don’t have a network connection, is an important use
case. Deep networks are very effective at this sort of task, and you
Understanding the Basics of TensorFlow | 5
剩余63页未读，继续阅读
Aimee喜欢吃蓝莓
- 粉丝: 3
- 资源: 11
我的内容管理
展开
最新资源
- zlib-1.2.12压缩包解析与技术要点
- 微信小程序滑动选项卡源码模版发布
- Unity虚拟人物唇同步插件Oculus Lipsync介绍
- Nginx 1.18.0版本WinSW自动安装与管理指南
- Java Swing和JDBC实现的ATM系统源码解析
- 掌握Spark Streaming与Maven集成的分布式大数据处理
- 深入学习推荐系统：教程、案例与项目实践
- Web开发者必备的取色工具软件介绍
- C语言实现李春葆数据结构实验程序
- 超市管理系统开发：asp+SQL Server 2005实战
- Redis伪集群搭建教程与实践
- 掌握网络活动细节：Wireshark v3.6.3网络嗅探工具详解
- 全面掌握美赛：建模、分析与编程实现教程
- Java图书馆系统完整项目源码及SQL文件解析
- PCtoLCD2002软件：高效图片和字符取模转换
- Java开发的体育赛事在线购票系统源码分析
资源上传下载、课程学习等过程中有任何疑问或建议，欢迎提出宝贵意见哦~我们会及时处理！
点击此处反馈
