Memristor-Based Edge Detection Dataset

This is the data produced for the paper titled: Memristor-Based Edge Detection. <br><br>In this study, we investigate the use of silicon dioxde memristors in edge detection. Devices exhibit analogue and volatile behaviours and are connected in potential divider arrangements. Encoding image pixels as spike trains and applying these to the memristors allow us to detect sharp changes in pixel intensity and in turn predict edges within an image. <br><br>The dataset contains data from: device characterisation, interpolated simulation models, output images generated in simulation and device variance data.<br> README files are included throughout the directories to explain the formatting and details of files. <br><br>

本数据集为论文《基于忆阻器（memristor）的边缘检测》（Memristor-Based Edge Detection）所生成的配套实验数据。

本研究探究了二氧化硅忆阻器（silicon dioxide memristors）在边缘检测任务中的应用。该类器件具备模拟特性与易失性，并以分压器（potential divider）架构进行互连。将图像像素编码为脉冲序列（spike trains）并输入至忆阻器中，可实现对像素强度突变的检测，进而完成图像内边缘的预测。

本数据集包含以下四类数据：器件表征数据、插值仿真模型数据、仿真生成的输出图像数据以及器件方差数据。各目录中均附带README文件，用于说明文件格式与相关细节。

搜集汇总

背景与挑战

背景概述

该数据集基于忆阻器的边缘检测研究，包含设备表征、仿真模型和输出图像等数据，用于分析二氧化硅忆阻器在计算机视觉中检测图像边缘的性能。数据集发布于2019年，覆盖电气工程和微电子学领域，采用CC0许可证开放共享。