滴水

改程序实现了对dalas的1-wire器件温度传感器ds18b20（也可以是ds1825）的驱动，并将温度值显示在液晶屏幕1602上-This program is dedicated to driving the 1-wire device ds18b20(ds1825),which reads the temperature and displays it on the LHD1602

科密一卡通二次开发文档以及动态库以及程序(test kemiykt sdk doc and dll files)

说明：  MMC模块多电平变换器学习资料 论文+仿真案例(MMC module multilevel converter learning materials paper + simulation case)

说明：  裂纹是典型的线结构，在许多计算机视觉应用中都很有趣。在实际应用中，路面裂缝等许多裂缝连续性差、对比度低，给利用低层特征进行基于图像的裂缝检测带来了很大的挑战。在本文中，我们提出了深度裂纹——一个端到端可训练的深度卷积神经网络，通过学习用于裂纹表示的高级特征来自动检测裂纹。该方法将在层次卷积阶段学习到的多尺度深度卷积特征融合在一起，以获取线路结构。更详细的表示在大比例尺的feature maps中进行，更全面的表示在小比例尺的feature maps中进行。我们在SegNet的编码器解码器架构上构建深度裂纹网，并对在相同尺度下在编码器网络和解码器网络中生成的卷积特征进行配对融合。(Cracks are typical line structures that are of interest in many computer-vision applications. In practice, many cracks, e.g., pavement cracks, show poor continuity and low contrast, which bring great challenges to image-based crack detection by using low-level features. In this paper, we propose DeepCrack---an end-to-end trainable deep convolutional neural network for automatic crack detection by learning high-level features for crack representation. In this method, multi-scale deep convolutional features learned at hierarchical convolutional stages are fused together to capture the line structures. More detailed representations are made in larger scale feature maps and more holistic representations are made in smaller scale feature maps. We build DeepCrack net on the encoder decoder architecture of SegNet and pairwisely fuse the convolutional features generated in the encoder network and in the decoder network at the same scale.)

自由软件 非常好的文本编译器-very good free software compiler version

说明：  有关分裂bregman方法的描述，采用分裂Bregman迭代的全变差盲反褶积(The split bregman method for L1 regularizen problem)

vb做的计算器，可以运行 vb做的计算器，可以运行-vb do calculators, can run vb do calculators, can run

使用ENVI IDL编程实现的交叉熵法阈值分割(Using IDL Programming to Realize Threshold Segmentation of Cross Entropy Method)

说明：  在ansys软件中通过编程对悬索结构进行找形及计算(shape finding of suspension cable structure)

nothing special. i m so tired