搜索资源列表
20070427105112594
- 基于DSP的手写数字识别系统.介绍了基于TMS320VC5402的手写数字识别系统和该系统的基本原理，给出了它的硬件原理图和软件设计程序框图。最后描述了所用的识别算法和改进的训练算法-DSP-based digital handwriting recognition system. Based on the number of handwritten TMS320VC5402 character recognition system and the system's basic prin
ocr0
- 基于人工神经网络的光学字符识别系统及硬件实现 研究了人工神经网络及光学字符识别的基本理论、一般方法： 对人工神经网络的发展、现状、理论做了深入的研究。重点研究了BP网络的原理、特点、应用方法。研究了脱机光学字符识别的方法、理论。重点研究了基于K-L变换的字符图像的特征抽取方法。 研究了基于ARM技术的嵌入式系统的构造、设计： 通过实际动手，研究了基于ARM技术的处理器的基本构造、使用方法；使用并比较了三星4510b、atmel at91rm9200芯片的性能；掌握了高频印刷
Perspective-accurate-classification-of-face-detect
- 精确分类的视角无关人脸检测方法与硬件加速体系结构Perspective accurate classification of face detection method has nothing to do with hardware acceleration architecture-Perspective accurate classification of face detection method has nothing to do with hardware acceleration a
jingbin123654
- 环境监控及红外遥控系统硬件原理及时序分析 -Environmental monitoring and infrared remote control system hardware and timing of the principle
moshishibie
- 模式识别是以应用为基础，目的是将图像进行分类。这些对象与应用领域有关，可以是图像、波形或者任何可测量且需要分类的对象。虹膜识别即为模式识别的一个主要应用，一个自动虹膜识别系统包含硬件和软件两大模块，虹膜图像获取装置和虹膜识别算法，分别对应于图像获取和模式匹配这两个基本问题。-Pattern recognition is based on the application purpose is to image classification. Related to the field with th
Face-Recgnition-on-FPGA
- 详细介绍了如何在FPGA上建立人脸识别系统，从硬件软件两方面做了说明，非常值得仔细阅读学习-Details how to build face recognition system on an FPGA, made from both hardware and software are described, well worth learning to read
BJX1560
- 台湾产的手写汉字识别芯片,硬件识别译码,可直接输出待选汉字编码.-Handwritten Chinese character recognition chip, produced in Taiwan recognized by the hardware decoding, can be directly output to be selected Chinese character encoding.
face-recongnition-hardware
- 这是一篇博士论文人脸识别的硬件实现全文理论脉络清晰易懂 -Face recognition hardware to achieve the full text of theoretical context lucid
Testcamera
- 图像采集程序 并可识别采集的图像中的圆形个体的程序 需要硬件网络相机的支持-The image acquisition process can identify the images collected round the individual program needs the support of the hardware network camera
ViBe
- ViBe是一种像素级视频背景建模或前景检测的算法，效果优于所熟知的几种算法，对硬件内存占用也少，很简单。-ViBe is a pixel-level video background modeling or prospects detection algorithm is better than several well-known algorithms, hardware memory footprint small, very simple.