<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Silvia Dias Almeida | IKIM MML</title><link>https://mml.kite.ume.de/authors/silvia-dias-almeida/</link><atom:link href="https://mml.kite.ume.de/authors/silvia-dias-almeida/index.xml" rel="self" type="application/rss+xml"/><description>Silvia Dias Almeida</description><generator>HugoBlox Kit (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Tue, 01 Apr 2025 00:00:00 +0000</lastBuildDate><item><title>Unlocking the potential of digital pathology: Novel baselines for compression</title><link>https://mml.kite.ume.de/publications/fischer-unlocking-2025/</link><pubDate>Tue, 01 Apr 2025 00:00:00 +0000</pubDate><guid>https://mml.kite.ume.de/publications/fischer-unlocking-2025/</guid><description/></item><item><title>Learned Image Compression for HE-Stained Histopathological Images via Stain Deconvolution</title><link>https://mml.kite.ume.de/publications/fischer-learned-2025/</link><pubDate>Wed, 01 Jan 2025 00:00:00 +0000</pubDate><guid>https://mml.kite.ume.de/publications/fischer-learned-2025/</guid><description/></item><item><title>Enhanced Diagnostic Fidelity in Pathology Whole Slide Image Compression via Deep Learning</title><link>https://mml.kite.ume.de/publications/fischer-enhanced-2024/</link><pubDate>Mon, 01 Jan 2024 00:00:00 +0000</pubDate><guid>https://mml.kite.ume.de/publications/fischer-enhanced-2024/</guid><description/></item></channel></rss>