Description: 联机数字手写识别，模式识别中很基础的程序，也是基于点轨迹的识别-Online digital handwriting recognition, pattern recognition, it is based on procedures, is also based on the identification of trajectory points Platform: |
Size: 261120 |
Author:wdx |
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Description: 内含公交系统,模式识别专业的分类程序,OPENGL的动态效果,简单的学生数据库管理程序和一个按照曲线轨迹动画程序,开发环境均为VC++6.0-Includes public transportation systems, pattern recognition classification of professional procedures, OPENGL dynamic effect, the simple student database management procedures and a trajectory curve in accordance with the animation process, development environment are VC++ 6.0 Platform: |
Size: 15512576 |
Author:dnf |
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Description: Trajectory Pattern Mining-This software is an implementation of the T-Pattern mining algorithm. Reference
paper is "Trajectory Pattern Mining", by F. Giannotti, M. Nanni, D. Pedreschi
and F. Pinelli, published on KDD 2007 conference.
This software is developed in C++.
Platform: |
Size: 644096 |
Author:warton |
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Description: Analysing patterns in gigantic and complex data: A motion pattern approach to mine frequent behaviors in trajectory data. Platform: |
Size: 6520832 |
Author:Leganola Aston |
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Description: 一个共同的视频被空间相关去噪的框架随机噪声和空间相关的固定模式噪声。首先，在每一卷的空间和时间上的相关性，利用sparsify数据在三维时空的变换域，然后3D体积的频谱系数的自适应阈值萎缩三维阵列。这样的阵列取决于特定的运动轨迹的体积，单个功率谱密度的随机和固定的模式噪声，以及噪声方差，自适应地估计在变换域。-The video was a common fixed pattern noise spatial correlation denoising framework random noise and space-related. First of all, in space and time correlation of each volume, use sparsify data in three-dimensional space transform domain adaptive threshold spectral coefficients 3D volume and shrinking three-dimensional array. Such an array depends on the particular trajectory volume, a single power spectral density of random and fixed pattern noise, and the noise variance, estimated adaptively transform domain. Platform: |
Size: 496640 |
Author:西门吹雪 |
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Description: 使用本章学习的K－平均算法，以颜色分量（或几何性状）作为坐标参数，对景象图进行聚类分析，要求最后的分类结果将路标（可能包括少量相似区域）聚类为一个模式类别。要求给出样本模式点，绘制坐标图（标出各个聚类中心的迭代移动轨迹），绘制算法框图，给出结论。并检查上机结果。-Use this learn K - average algorithm to color components (or geometric characters) as coordinate parameters, clustering analysis was carried out on the scene graph, for the final classification result will sign (may include a small amount of similar areas) clustering pattern for a category.Ask for sample model, map coordinates (mark iterative moving trajectory of every clustering center), rendering algorithm block diagram, the conclusion are given.And check the computer results. Platform: |
Size: 1727488 |
Author:张煊宜 |
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Description: Geolife GPS 轨迹数据集–用户指南
这一 GPS 轨迹数据集是在 (微软研究亚洲) Geolife 项目中收集的, 178 用户在四年 (2007年4月至 2011年10月) 期间。该数据集的 GPS 轨迹由一个时间戳点序列表示, 每一个都包含纬度、经度和高度信息。该数据集包含17621个轨迹, 总距离为1251654公里, 总持续时间为48203小时。该轨迹数据集可以应用于移动模式挖掘、用户活动识别、基于位置的社交网络、位置隐私和位置推荐等多个研究领域。(Geolife GPS track data set - User Guide The GPS trajectory data set was gathered in the Geolife project (Microsoft Research Asia) and 178 users over a four-year period (April 2007 to October 2011). The GPS trajectory of the data set is represented by a sequence of time stamps, each of which contains latitude, longitude and altitude information. The dataset contains 17621 trajectories with a total distance of 1251654 km and a total duration of 48203 hours. These trajectories record different GPS loggers and GPS telephones, and have various sampling rates. The trajectory of 91% is recorded in dense representation, for example, every 1 to 5 seconds or 5 to 10 meters per point. The trajectory data set can be used in many research fields, such as mobile pattern mining, user activity recognition, location-based social networks, location privacy and location recommendation.) Platform: |
Size: 22576128 |
Author:李白43 |
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Search - Trajectory Pattern