支持IC卡数据一键分析、数据对比、数据修改、日期转换、校验计算（支持28种校验计算如XOR、ADD、NOT、CRC、MD）非常好用，是IC数据分析中不可或缺的一款工具。

在未配对的图像到图像翻译（NEGCUT）中进行对比学习的实例式硬负示例生成 它是在不成对的图像到图像转换（NEGCUT）中进行对比学习的实例化硬否定示例生成的官方PyTorch实现。

OpenCV 畸变校正函数undistortPoints()与remap()校正效果对比程序，包含完整程序、程序所用图片、内参标定结果、程序测试结果

u-boot的board_init_f和board_init_r阶段执行任务的对比

支持两个视频分辨率和视频内容的对比

好用的代码对比工具。好用的代码对比工具。好用的代码对比工具。好用的代码对比工具。

目标检测算法的介绍 In recent years, Convolutional Neural Network (CNN) has been widely applied in computer vision tasks and has achieved significant improvement in image object detection. The CNN methods consume more computation as well as storage, so GPU is introduced for real-time object detection. However, due to the high power consumption of GPU, it is difficult to adopt GPU in mobile applications like automatic driving. The previous work proposes some optimizing techniques to lower the power consumption of object detection on mobile GPU or FPGA. In the first Low-Power Image Recognition Challenge (LPIRC), our system achieved the best result with mAP/Energy on mobile GPU platforms. We further research the acceleration of detection algorithms and implement two more systems for real-time detection on FPGA with higher energy efficiency. In this paper, we will introduce the object detection algorithms and summarize the optimizing techniques in three of our previous energy efficient detection systems on different hardware platforms for object detection.

摘要：为研究不同的冗余方式对本安电源双重化保护电路的影响，在一种新型截流保护电路的基础上，分别对其进行双重化串联和并联连接，在模拟一个故障前提下，进行对比试验。

将SimpleJSON,jsoncpp,libjson,rapidjson放在同一个vs2010的工程中,给出了一个简单的性能测试代码.

memcache、redis、tair性能对比测试报告.docx