资源列表
神经网络讲义+电子教案
- 神经网络讲义+电子教案(书籍/资料/PPT)(Neural network lecture + electronic teaching case (book / data /PPT))
net
- 本课件是matlab神经网络的讲义并附带有数学建模题目共实践用,非常给力的资料-The courseware is the matlab neural network together with the mathematical modeling lecture topics were practical use, the information is to force
Computer-vision-based-lpr-System
- 计算机视觉是一门研究如何使机器“看”的科学,更进一步的说,就是是指用摄影机和电脑代替人眼对目标进行识别、跟踪和测量等机器视觉,并进一步做图形处理,用电脑处理成为更适合人眼观察或传送给仪器检测的图像。作为一个科学学科,计算机视觉研究相关的理论和技术,试图建立能够从图像或者多维数据中获取‘信息’的人工智能系统。这里所 指的信息指Shannon定义的,可以用来帮助做一个“决定”的信息。因为感知可以看作是从感官信号中提 取信息,所以计算机视觉也可以看作是研究如何使人工系统从图像或多维数据中“感知”的科学
CNN2-数字识别
- 利用C写的一个用卷积神经网络做数字识别程序(Using C to write a convolution neural network to do digital identification procedures)
CNN2
- 基于Mnist库的手写数字识别的C++源代码,用CNN实现,并且建立了用户界面-Handwritten numeral recognition Mnist library C++ source code, using CNN achieve, and the establishment of a user interface
LightNet-master
- 目前最轻量级别的深度学习源码,采用CNN实现高精度识别,与目前流行的Caffe相比,具有实现灵活,可迁移程度高等优势,值得深入学习!-Currently the lightest level of deep learning source, using CNN to achieve high-precision identification, compared with the current popular Caffe, with the realization of flexible, hi
Minning-of-Massive-Datasets
- 斯坦福数据挖掘理论的详细介绍,很有条理,很全面,而且有用到当下最流行的编程模型mapreduce-Stanford data mining theory in detail, very organized, very comprehensive, and useful to present the most popular programming model mapreduce
m
- 一种双聚类算法的实现与改进,通过对双聚类算法的优化来改进-A double-clustering algorithm to achieve and improve, through the double-clustering algorithm optimization to improve
afsa_alg
- 基于VC6.0设计的界面,算是新手上手的好参考! 都是我自己琢磨的哦! 如果有问题,请发邮件到hoomin712@163.com -VC6.0 based interface design, considered a novice to get started is a good reference!
svmlight-6.01
- 这个源码是用来学习支持向量机的,里面包含了多核函数。-This source is used to support vector machine learning, which includes multi-core function.
yichuansuanfa_lunwen
- 基于遗传算法的试题库智能组卷研究,本文提出了三种利用遗传算法智能组卷的方法。
车牌汉字样本
- 车牌识别中汉字训练样本,包含31个省份,每个字符几十到几百个样本。(License plate recognition Chinese character training samples, including 31 provinces, each character tens to hundreds of samples.)