搜索资源列表
orc
- 基于C++的HALCON图像处理 简单的数字，字符识别 带神经网络图训练-Based C++ of HALCON image processing simple numeric character recognition with neural network diagram Training
zifushibie
- 基于神经网络的字符识别。利用神经网络算法在c语言下实现车牌字符的智能识别。-Character recognition based on neural network. Using neural network algorithm to realize the intelligent recognition of license plate characters in C language.
BPrecognition
- BP神经网络识别手写字符验证码，包括10721张字母、数字样本-BP neural network handwritten character recognition codes, including 10,721 letters, numbers, samples
bp-for-license-recognition
- 利用BP神经网络算法进行车牌图像识别的代码，进行数字、车牌字符的识别，另附相应学习图片素材（二值化）及训练后网络-Using BP neural network algorithm for vehicle license plate image recognition code, the number of characters, license plate recognition, with the corresponding learning picture material and tra
BP
- 基于VC++的BP神经网络，用于识别数字字符，亲测可用。-VC++ based on BP neural network for identifying numeric characters, pro-test available.
charSamples
- 车牌识别样本库。每个字符库有50个样本，用于测试。用于车牌识别神经网络库的训练样本。(License plate identification sample library. Each character library has 50 samples for testing. Training samples for license plate recognition neural network library.)
code&doc
- 基础的卷积神经网络代码，实现mnist手写字符识别，含中文文档说明(Basic CNN code, including detailed annotation in Chinese)
2_tf_mnist
- tensorflow，简单神经网络识别手写字符(Recognition of handwritten characters by neural network)
code(BP_to_MNIST)
- 使用BP神经网络实现手写字符库MNIST的识别。(The recognition of handwritten character library MNIST is realized by using BP neural network.)
first
- 车牌定位 车牌分割 字符识别 正如上面所讲,车牌识别主要分为3个部分,其中第一部分车牌定位,一般采用颜色定位,特征定位等,这方面一堆资料我就不写了.分割一般采用投影法.识别的话方法就比较多了,有模板匹配,bp神经网络,卷积神经网络等.(pan.baidu.com/s/1jIdSuXK)