bezier-surface-master

说明：  非均匀有理B样条 第2版.pdf NURBS理论经典书籍(The nurbs book(second edition) NURBS Theory Classic Books)

Laws纹理策度是用来进行纹理分割的程序,这种方法很有用.(Laws degree texture strategy are used for texture segmentation procedure, this method useful.)

运用图像处理，运用滤波，闭运算，腐蚀，膨胀进行一维码即条形码的识别(The use of image processing, the use of filtering, closed computing, corrosion, expansion of one-dimensional code, that is, bar code identification)

说明：  计算机图形学初级学者（教科书画法）中点画圆算法(computer graphics beginner (textbook method), the algrithm of middle point circle-drawing.)

说明：  这个是在运行的时候为了调试而写的，主要应用的场合是循环多，跟踪不方便的时候，记录到日志，引用了一个单元Unit_HBase,Unit_LogSp，已上传(this is the time to run the debugger and writing, the main application is a revolving occasions, tracking inconvenient time to record log, quoted a unit Unit_HBase, Unit_LogSp, uploaded)

说明：  QT webview浏览器相关开发，简单webview应用开发(QT WebView browser related development, simple WebView application development)

matlab中值平滑处理,主要是用5点平滑和3点平滑实现(matlab median smoothing was used in 5-point smoothing and 3 points to achieve smooth)

基于ESS303开发板的OV7670_VGA拍照功能实现(Implementation of OV7670_VGA camera function based on ESS303 development board)

3d点云的显示与变深度图，visual C++ 代码(he display and variable depth map of 3D point cloud)

说明：  UNet最早发表在2015的MICCAI上，短短3年，引用量目前已经达到了4070，足以见得其影响力。而后成为大多做医疗影像语义分割任务的baseline，也启发了大量研究者去思考U型语义分割网络。而如今在自然影像理解方面，也有越来越多的语义分割和目标检测SOTA模型开始关注和使用U型结构，比如语义分割Discriminative Feature Network(DFN)(CVPR2018)，目标检测Feature Pyramid Networks for Object Detection(FPN)(CVPR 2017)等。(Its influence has reached 70% in 2015. Then it became the baseline that most of the medical image semantic segmentation tasks, and inspired a large number of researchers to think about the U-shaped semantic segmentation network. In the aspect of natural image understanding, more and more SOTA models of semantic segmentation and object detection begin to pay attention to and use U-shaped structure, such as semantic segmentation, discriminative feature network (DFN) (cvpr2018), feature pyramid networks for object detection (FPN) (CVPR 2017), etc.)