小秋SLAM笔记

alphakappa-Detection-PyTorch-Notebook-master

基于相机的2D特征跟踪 这是功能跟踪模块，用于评估自动车辆碰撞检测系统的各种检测器/描述符组合。 该项目包括四个部分： 加载图像，设置数据结构并将所有内容放入环形缓冲区以优化内存负载。 集成了几个关键点检测器，例如HARRIS，FAST，BRISK和SIFT，并就关键点数量和速度进行了比较。 使用蛮力以及FLANN方法提取和匹配描述符。 以不同的组合测试各种算法，并就某些性能指标进行比较。 本地运行的依赖项 cmake> = 2.8 所有操作系统： make> = 4.1（Linux，Mac），3.81（Windows） Linux：大多数Linux发行版默认都安装了make Mac： Windows： OpenCV> = 4.1 必须使用-D OPENCV_ENABLE_NONFREE=ON cmake标志从源代码进行编译，以测试SIFT和SURF检测器。 Open

人脸识别AI 借助AI，它可以检测人脸 预习 它是使用AI库制作的 享受您功能强大的应用程序

Detection of Alzheimer's disease and mild cognitive impairment based on structural volumetric MR images using 3D-DWT and WTA-KSVM trained by PSOTVAC

SNKC: An Efficient On-the-fly Pollution Detection Scheme for Content Distribution with Linear Network Coding

Pedestrian detection is a fundamental problem in video surveillance. An overwhelming majority of existing detection methods are based on sliding windows with exhaustive multi-scale scanning over the whole frame images which can achieve good accuracy but suffer from expensive computational cost. To reduce the complexity significantly while keeping high accuracy, in this paper, we propose an effective and efficient pedestrian detection method based on sliding windows with well-designed multi-scale

On-site oral fluid testing for drugs of abuse has become prominent in order to take immediate administrative action in an enforcement process. Herein, we report a DVD technology-based indirect competitive immunoassay platform for the quantitative detection of drugs of abuse. A microfluidic approach

《Histograms of Oriented Gradients for Human Detection》论文原文，作者：Navneet Dalal and Bill Triggs，HOG特征的论文出处

经典论文《Histograms of Oriented Gradients for Human Detection》的解读，内附一小段示例代码（Python），著名的HOG方法就源于这篇论文