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    <title>OMR on Bdim</title>
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    <copyright>2021-CURRENT_YEAR Bdim</copyright>
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      <title>OMR Related Paper Review: Practical End-to-End Optical Music Recognition for Pianoform Music</title>
      <link>/posts/omr-related-paper-review-practical-end-to-end-optical-music-recognition-for-pianoform-music/</link>
      <pubDate>Tue, 27 Aug 2024 00:01:11 +0800</pubDate>
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      <description>&lt;h2 id=&#34;core-ideas&#34;&gt;Core Ideas&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;1. Background of the Study:&lt;/strong&gt;&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;This paper explores how to implement an end-to-end Optical Music Recognition (OMR) system using deep learning methods, with a focus on recognizing pianoform music. While recent progress has been made in monophonic music recognition, existing OMR models struggle to handle the multi-voice and multi-staff nature of piano music.&lt;/li&gt;
&lt;li&gt;The complexity of piano music stems from its independent parallel voices, which can freely appear and disappear within a composition. This complexity introduces additional challenges for the output of OMR models.&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;&lt;strong&gt;2. Key Contributions:&lt;/strong&gt;&lt;/p&gt;</description>
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