<?xml version="1.0" encoding="utf-8" standalone="yes" ?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
  <channel>
    <title>边缘增强 | ViLab</title>
    <link>https://vilab.team/tag/%E8%BE%B9%E7%BC%98%E5%A2%9E%E5%BC%BA/</link>
      <atom:link href="https://vilab.team/tag/%E8%BE%B9%E7%BC%98%E5%A2%9E%E5%BC%BA/index.xml" rel="self" type="application/rss+xml" />
    <description>边缘增强</description>
    <generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Sun, 01 Oct 2023 00:00:00 +0000</lastBuildDate>
    <image>
      <url>https://vilab.team/media/icon_hu2896232876136423579.png</url>
      <title>边缘增强</title>
      <link>https://vilab.team/tag/%E8%BE%B9%E7%BC%98%E5%A2%9E%E5%BC%BA/</link>
    </image>
    
    <item>
      <title>Eoformer: Edge-oriented transformer for brain tumor segmentation</title>
      <link>https://vilab.team/publication/eoformer-edge-oriented-transformer-for-brain-tumor-segmentat/</link>
      <pubDate>Sun, 01 Oct 2023 00:00:00 +0000</pubDate>
      <guid>https://vilab.team/publication/eoformer-edge-oriented-transformer-for-brain-tumor-segmentat/</guid>
      <description>&lt;p&gt;本文提出边缘导向Transformer（EoFormer），用于脑肿瘤MRI图像分割。该方法采用CNN-Transformer混合编码器，CNN提取局部低级特征，Transformer建模长距离依赖以生成全局高级特征；解码器集成边缘导向Sobel与Laplacian锐化模块，增强边缘信息。同时引入高效注意力与重参数化技术，提升特征表示能力与分割精度。&lt;/p&gt;
</description>
    </item>
    
  </channel>
</rss>
