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Confocal Fluorescence Microscopy

Confocal Fluorescence Microscopy

Confocal microscopy is an advanced microscopic technique. The prime advantage of the confocal microscope over other microscopy techniques is its ability to block the out-of-focus light from the illuminated samples using pinholes. It is widely used with fluorescence optics to obtain high-resolution, sharp contrast images. Unlike optical microscopes, confocal microscopes use a focused beam of light laser to scan the entire sample surface at different z-planes. These microscopes are, therefore,...

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相关实验视频

Updated: Jun 25, 2025

Simultaneously Capturing Real-time Images in Two Emission Channels Using a Dual Camera Emission Splitting System: Applications to Cell Adhesion

Simultaneously Capturing Real-time Images in Two Emission Channels Using a Dual Camera Emission Splitting System: Applications to Cell Adhesion

Published on: September 4, 2013

基于时间划分多重复合的 LiDAR 应用的多光谱语义摄像头.

Sehyeon Kim¹, Tae-In Jeong¹, San Kim¹

¹Department of Cogno-Mechatronics Engineering, College of Nanoscience and Nanotechnology, Pusan National University, Busan, 46241, Republic of Korea.

Scientific reports

|May 20, 2024

概括

此摘要是机器生成的。

这项研究引入了一个新的多光谱LiDAR系统,使用时间分割复杂化来增强对象识别. 该系统同时捕获空间和光谱数据,提高自动驾驶应用的准确性.

关键词:

李达尔 (LiDAR) 是一种激光雷达.多光谱摄像机多光谱摄像机时间划分多重复合.飞行时间飞行时间

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Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Published on: February 12, 2014

Multiplex Chemical Imaging Based on Broadband Stimulated Raman Scattering Microscopy

Multiplex Chemical Imaging Based on Broadband Stimulated Raman Scattering Microscopy

Published on: July 25, 2022

相关实验视频

Last Updated: Jun 25, 2025

Simultaneously Capturing Real-time Images in Two Emission Channels Using a Dual Camera Emission Splitting System: Applications to Cell Adhesion

Simultaneously Capturing Real-time Images in Two Emission Channels Using a Dual Camera Emission Splitting System: Applications to Cell Adhesion

Published on: September 4, 2013

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Published on: February 12, 2014

Multiplex Chemical Imaging Based on Broadband Stimulated Raman Scattering Microscopy

Multiplex Chemical Imaging Based on Broadband Stimulated Raman Scattering Microscopy

Published on: July 25, 2022

科学领域:

机器人技术和自主系统
光学工程是指光学工程.
人工智能的人工智能

背景情况:

基于飞行时间 (TOF) 的光检测和测距 (LiDAR) 系统对于自主识别至关重要,可以高精度地绘制环境.
当前的LiDAR系统在对象错误识别方面扎,需要改进识别能力.
多光谱LiDAR,特别是短波红外 (SWIR) 范围,提供了增强的材料信息,但面临复杂性和成本挑战.

研究的目的:

开发一种新的,紧的多光谱LiDAR系统,用于语义对象推理.
使用单个光探测器,同时获取空间,光谱和TOF距离数据.
提高自主系统中对象识别的准确性和可靠性.

主要方法:

提出了一个基于时间分割多重复制 (TDM) 的多光谱LiDAR系统.
用五种不同的SWIR波长的纳秒脉冲来同时获取数据.
使用RGB颜色编码的多光谱图像和用卷积神经网络 (CNN) 进行分类来证明识别.

主要成果:

成功获得了同时的空间,光谱和TOF距离信息,使光学损失最小化.
视觉化了各种手工材料 (人,人形,手套,打印) 的光谱差异,以不同的RGB颜色.
使用CNN模型实现了多光谱数据的有效分类.

结论:

基于TDM的多光谱LiDAR系统为增强的对象识别提供了一个紧且具有成本效益的解决方案.
这项技术显著改善了物质信息的获取,解决了传统LiDAR的局限性.
该系统具有很大的潜力,可以提高自动驾驶和机器人技术的安全性和可靠性.