摘要
手写小车系统是由手写数字识别系统和智能小车硬件平台两部分组成。其中手写数字识别系统采用神经网络算法训练手写数据集,在图片特征与数据集类似的情况下其识别准确率达到了98%以上。在智能小车的硬件系统中,小车能够完成前景、后退、寻迹、转向以及避障等功能。此外,整个手写数字识别小车系统在电脑端完成对数字的识别,然后通过无线蓝牙将识别的结果传输给智能小车,小车根据其识别的指令做出相应的响应动作。
The handwritten car system is composed of two parts,the handwritten number recognition system and the smart car hardware platform.Among them,the handwritten digit recognition system uses neural network algorithms to train the handwritten data set,and its recognition accuracy reaches more than 98% when the picture features are similar to the data set.In the hardware system of the smart car,the car can complete functions such as foreground,backward,tracing,steering,and obstacle avoidance.In addition,the entire handwritten number recognition car system completes the recognition of numbers on the computer side,and then transmits the recognition results to the smart car through wireless Bluetooth,and the car makes corresponding response actions according to the recognized instructions.
作者
杜兴
Du Xing(GuiZhou Vocational Technology College of Electronics&Information,Kaili Guizhou,556000)
出处
《电子测试》
2022年第6期8-10,共3页
Electronic Test
关键词
手写数字识别
神经网络
小车控制
无线蓝牙
Handwritten digit recognition
Neural Networks
Car control
wireless bluetooth
