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PowerPredict
- 本文采用模糊数学和优化理论建立起一套预测模型由计算机自动预测电力负荷从而保证了预测结果的正确性和可信度通过对深圳市远景年电量预测的实例表明该方法是可行而有效的 -this fuzzy optimization theory and mathematical model to establish a set automatically by a computer forecasting electricity load so guarantee the accuracy of the resu
Ubuntu_10.04
- 学习Ubuntu_10.04当前电子技术突飞猛进的发展，各种芯片在微型计算机发展中起到里不可替代的作用，而且芯片的多种功能与其灵活的应用方式相结合所解决的实际问题已经强烈地吸引着广大电子爱好者的眼光。-Learning Ubuntu_10.04 current rapid development of electronic technology, the development of a variety of chips in the micro-computer to play an irre
etection
- 双目视觉技术在计算机辅助检测中的应用-Binocular vision technology in computer-aided detection
hough-transform
- Circles are a common geometric structure of interest in computer vision applications. The use of the Hough transform to locate circles will be explained and demonstrated. This is a particular example of the use the Hough transform to search a p
egqyy
- 非常适合计算机视觉方面的研究使用,独立成分分析算法降低原始数据噪声，车牌识别定位程序的部分功能。- Very suitable for the study using computer vision, Independent component analysis algorithm reduces the raw data noise, Part of the license plate recognition locator feature.
qj117
- 关于神经网络控制，本程序的性能已经超过其他算法，非常适合计算机视觉方面的研究使用。- On neural network control, This program has exceeded the performance of other algorithms, Very suitable for the study using computer vision.
cedbk
- 基于K均值的PSO聚类算法,非常适合计算机视觉方面的研究使用,包括最小二乘法、SVM、神经网络、1_k近邻法。- K-means clustering algorithm based on the PSO, Very suitable for the study using computer vision, Including the least squares method, the SVM, neural networks, 1 _k neighbor method.
hxsga
- ldpc码的编解码实现，含噪脉冲信号进行相关检测,非常适合计算机视觉方面的研究使用。- Codec ldpc code implementation Noisy pulse correlation detection signal, Very suitable for the study using computer vision.
cs828
- 是本科毕设的题目，非常适合计算机视觉方面的研究使用,IMC-PID是利用内模控制原理来对PID参数进行计算。- The title of the commercial is undergraduate course you Very suitable for the study using computer vision, The IMC- PID is using the internal model control principle for PID parameters is calcul
1666
- 考虑雨衰 阴影 和多径影响，PLS部分最小二乘工具箱,非常适合计算机视觉方面的研究使用。- Consider shadow rain attenuation and multipath effects PLS PLS toolbox, Very suitable for the study using computer vision.
dx565
- 非常适合计算机视觉方面的研究使用,窗函数法设计一个数字带通FIR滤波器，计算目标和海洋回波的功率谱密度。- Very suitable for the study using computer vision, A window function design FIR digital band-pass filter, Calculating a target and ocean echo power spectral density.
ntuhu
- 通过虚拟阵元进行DOA估计，非常适合计算机视觉方面的研究使用,欢迎大家下载学习。- Conducted through virtual array DOA estimation, Very suitable for the study using computer vision, Welcome to download the study.
Harris-detection-amd-matching-corner
- 使用Harris角点检测，然后使用RANSA算法进行相应的match匹配算法，主要应用在计算机视觉以及opencv中-Harris corner detection and match corresponding corner points by match algorithm and RANSA algorithm in computer vision and openCV
xb541
- GPS和INS组合导航程序，非常适合计算机视觉方面的研究使用,具有丰富的参数选项。- GPS and INS navigation program, Very suitable for the study using computer vision, It has a wealth of parameter options.
kgjdx
- 已调制信号计算其普相关密度，FIR 底通和带通滤波器和IIR 底通和带通滤波器，非常适合计算机视觉方面的研究使用。- Modulated signals to calculate its density Pu-related, Bottom-pass and band-pass FIR and IIR filter bottom pass and band-pass filter, Very suitable for the study using computer vision.
gunfaiyan
- 数学方法是部分子空间法，独立成分分析算法降低原始数据噪声，非常适合计算机视觉方面的研究使用。- Mathematics is part of the subspace, Independent component analysis algorithm reduces the raw data noise, Very suitable for the study using computer vision.
-林达华博客内容
- 学者林达华的博客的内容，很好的计算机视觉方面的资料。(Scholar Lin Dahua's blog content, good computer vision information.)
深度卷积神经网络
- 作为类脑计算领域的一个重要研究成果，深度卷积神经网络已经广泛应用到计算机视觉、自然语言处理、信息检索、语音识别、语义理解等多个领域，在工业界和学术界掀起了神经网络研究的浪潮，促进了人工智能的发展。卷积神经网络直接以原始数据作为输入，从大量训练数据中自动学习特征的表示。(As the important research achievement, deep convolutional neural networks have been widely applied to various fiel
Guided filter
- guided filter is for computer vision and application.
2017年中国计算机视觉行业研究报告
- 2017年行业状况及预测之后的发展，现在遇到的瓶颈，当前这方面比较好的公司，以及计算机视觉有关的领域(In 2017, the industry situation and the development after prediction, and now faced with bottlenecks, the current relatively good companies, as well as areas related to computer vision.)