相关实验视频

Updated: Jul 16, 2025

Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals
00:07

Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals

Published on: August 22, 2019

8.1K

SSTF-Unet:基于空间光谱变压器的U-Net用于高分辨率的高光谱图像采集

Haibo Liu, Chenguo Feng, Renwei Dian

    IEEE transactions on neural networks and learning systems
    |September 22, 2023
    PubMed
    概括

    本研究介绍了一种基于空间光谱变压器的新型U-Net (SSTF-Unet),用于将低分辨率的超光谱图像与高分辨率的多光谱图像融合. 新方法有效地捕捉全球特征,优于现有的高分辨率超谱图像生成方法.

    更多相关视频

    Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography04:48

    Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

    Published on: November 30, 2022

    2.8K
    Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters07:05

    Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

    Published on: June 18, 2021

    2.5K

    相关概念视频

    Upsampling01:22

    Upsampling

    Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
    254