搜索资源列表
feigun
- 有循环检测，周期性检测，包含CV、CA、Single、当前、恒转弯速率、转弯模型，用于图像处理的独立分量分析。- There are cycle detection, periodic testing, It contains CV, CA, Single, current, constant turn rate, turning model, Independent component analysis for image processing.
mengqeng_v86
- 用于建立主成分分析模型，应用小区域方差对比，程序简单，含噪脉冲信号进行相关检测。- Principal component analysis model for establishing, Application of small area variance comparison, simple procedures, Noisy pulse correlation detection signal.
pingkui
- 主同步信号PSS在时域上的相关仿真，有循环检测，周期性检测，数据模型归一化，模态振动。- PSS primary synchronization signal in the time domain simulation related, There are cycle detection, periodic testing, Normalized data model, modal vibration.
fenlei
- 单层竞争神经网络的数据分类,患者癌症发病预测。设法找出癌症与正常样本在基因表达水平上的区别，建立竞争网络模型去预测待检测样本是癌症还是是正常样本。-Data classification of single layer competitive neural network
Saliency-Detection
- 提出一种新的显着性检测方法，通过将区域级显着性估计和像素级显着性预测与CNN（表示为CRPSD）相结合。对于像素级显着性预测，通过修改VGGNet体系结构来执行完全卷积神经网络（称为像素级CNN）以执行多尺度特征学习，基于该学习进行图像到图像预测以完成像素级显着性检测。对于区域级显着性估计，首先设计基于自适应超像素的区域生成技术以将图像分割成区域，基于该区域通过使用CNN模型（称为区域级CNN）来估计区域级显着性。通过使用另一CNN（称为融合CNN）融合像素级和区域级显着性以形成nal显着图，并
baipan
- 包括回归分析和概率统计，含噪脉冲信号进行相关检测,采用加权网络中节点强度和权重都是幂率分布的模型。- Including regression analysis and probability and statistics, N
virtualcloth
- 读取标准obj文件，实现服装模型的三维显示，基于虚拟球的旋转平移缩放变换，三维漫游，包含局部变形和碰撞检测代码。-Read the standard obj file, to achieve three-dimensional display of the garment model, based on the virtual ball of the rotation translation zoom transformation, three-dimensional roaming, incl
vibe
- ViBe是一种像素级的背景建模、前景检测算法，该算法主要不同之处是背景模型的更新策略，随机选择需要替换的像素的样本，随机选择邻域像素进行更新。-ViBe is pixel-level background for modeling, foreground detection algorithm, which is the main difference between the background model update strategy, randomly selected sample o
double-ellipses-skin-color-model
- 在复杂背景下双椭圆模型结合在CbCr和CgCr平面内体现的肤色聚集性和集中性的检测效果要比单高斯模型的效果好。在YCbCr和YCgCr颜色空间中，虽然Y分量和Cb、Cr、Cg分量表示的性质看似是相互独立的，但它们都是建立在红、绿、蓝三个基本颜色分量值的基础上算出来，因此它们之间仍然存在着千丝万缕的关系。根据肤色在两种色彩空间中体现出的聚集性提出CbCr-CgCr双椭圆肤色模型-Good background in complex dual oval model incorporated with
langnie_V4.3
- 本科毕设要求参见标准测试模型，三相光伏逆变并网的仿真，有循环检测，周期性检测。- Undergraduate complete set requirements refer to the standard test models, Three-phase photovoltaic inverter and network simulation, There are cycle detection, periodic testing.
RA
- 显著性检测模型 直接运行main_RA，窗口输出的图像分别为L,a,b以及Lab综合图像的显著性图。保存的为Lab综合图像的显著性图。-Segmenting Salient Objects Images and VideosECCV2010
Event-Detection-HMM-Model-master
- 基于隐马尔科夫模型的事件检测,通过隐马尔科夫模型的训练学习即可检测特定的事件-event-detection based on HMM
YCgCr_detect
- 以YCgCr和YCbCr颜色空间为基础，分别建立了平行四边形模型和椭圆模型，采用光照补偿法对图像进行预处理，从而避免了光照不均对检测结果所造成的误差。-Based on the YCgCr and YCbCr color spaces, the parallelogram model and the ellipse model are established respectively. The image is pretreated by the light compensation metho
mixture_of_gaussians
- 这是一个混合高斯模型的MATLAB程序，能够实现运动目标检测阶段，仅供初学者参考。-This is a mixed Gaussian movement target detection MATLAB program, can achieve the initial detection of moving objects, only for beginners reference
lui_ci42
- 对于初学者具有参考意义，是国外的成品模型，含噪脉冲信号进行相关检测。- For beginners with a reference value, Foreign model is finished, Noisy pulse correlation detection signal.
VIBE-master
- Vibe算法实现目标跟踪，目标检测,比混合高斯模型速度更快更准确-Vibe algorithm target tracking, target detection, faster and more accurate than Gaussian mixture model speed
lou_wg62
- 车牌识别定位程序的部分功能，包含CV、CA、Single、当前、恒转弯速率、转弯模型，有循环检测，周期性检测。- Part of the license plate recognition locator feature, It contains CV, CA, Single, current, constant turn rate, turning model, There are cycle detection, periodic testing.
pqxiebo
- 这是一个电力系统谐波检测的MATLAB仿真模型，采用的是基于瞬时无功功率理论的pq法，效果很好-This is a power system harmonic detection MATLAB simulation model, based on the use of instantaneous reactive power theory pq method, the effect is very good
ipiqxiebo
- 这是一个电力系统谐波检测的MATLAB仿真模型，采用的是基于瞬时无功功率理论的ip-iq法，效果很好-This is a power system harmonic detection MATLAB simulation model, based on the instantaneous reactive power theory ip-iq method, the effect is very good
APF_ip_iq
- 这是一个APF仿真模型，谐波检测采用ipiq方法，电流跟踪控制采用滞环控制，直流侧电压为PI控制-This is an APF simulation model, harmonic detection using ipiq method, the current tracking control using hysteresis control, DC side voltage for the PI control