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tensorflow test

于 2020-11-22 发布

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代码说明：

说明：基于TensorFlow图像处理的小测试，里面的代码自己尝试过都可以运行。(Based on the TensorFlow image processing test, the code can run if it has tried.)

文件列表：

tensorflow test, 0 , 2019-03-01
tensorflow test\.idea, 0 , 2019-03-01
tensorflow test\.idea\inspectionProfiles, 0 , 2019-02-28
tensorflow test\.idea\inspectionProfiles\profiles_settings.xml, 228 , 2019-02-28
tensorflow test\.idea\misc.xml, 226 , 2019-02-28
tensorflow test\.idea\modules.xml, 282 , 2019-02-28
tensorflow test\.idea\tensorflow test.iml, 459 , 2019-02-28
tensorflow test\.idea\workspace.xml, 29848 , 2019-03-01
tensorflow test\data flow.py, 434 , 2019-02-28

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SFS_3
论文介绍了一种SFS 算法的参数估计及其实现。它在考虑自遮掩影响的情况下, 有效地估计了SFS 算法中涉及的各种控制参数, 并引入亮度约束、灰度梯度约束和可积性约束, 计算出表面高度和表面向量, 实现三维重构。最后还指出了在Matlab 中实现需要注意的问题。(The paper introduced a SFS algorithm parameter estimation and its implementation. It under the condition of considering the covering effect, estimates the SFS algorithm effectively involved in all kinds of control parameters, and introduces brightness constraint, gray level gradient constraint and the integrability of constraints, calculate the surface height and surface vector, realize the three-dimensional reconstruction. Finally, points out the problems requiring attention is realized in Matlab. )

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图像质量评价代码，用于评估两副图片的相似度(Image quality evaluation)

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采用了Harrtraining和离子滤波算法实现了拥挤人群人头计数，非常有用。VC++和Opencv开发，采用Oepncv中的Harrtraining训练一个分类器即可运行(Human detection and tracking in high density crowds is an unsolved problem. Standard preprocessing techniques such as background modeling fail when most of the scene is in motion. We integrate human detection and tracking into a single framework, and in- troduce a conrmation-by-classication method to estimate condence in a tracked trajectory, track humans through occlusions, and eliminate false positive detections.)

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陆吾生教授的压缩感知材料，PPT格式，开始学习基础知识的同学有帮助。(Professor Lu Wusheng compressed sensing materials, PPT format.)

2012-12-20 10:11:35下载

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拉普拉斯边缘检测与图像增强，Matlab6.5实现的.m文件，附有原图、检测到的边缘图和增强后的图。(Laplacian edge detection and image enhancement, Matlab6.5 of implementation. M file, with image, detected and enhanced edge map after the map.)

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tensorflow test

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