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	<title>
	Comments on: [转载][翻译] 卷积神经网络的直观解释	</title>
	<atom:link href="https://www.coder4.com/archives/5962/feed" rel="self" type="application/rss+xml" />
	<link>https://www.coder4.com/archives/5962</link>
	<description>Keep It Simple and Stupid</description>
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		<title>
		By: robber run		</title>
		<link>https://www.coder4.com/archives/5962#comment-22299</link>

		<dc:creator><![CDATA[robber run]]></dc:creator>
		<pubDate>Tue, 15 Sep 2026 07:20:23 +0000</pubDate>
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					<description><![CDATA[This translation actually makes the backprop diagram way clearer than the original English version. The way they explain the gradient flow in the pooling layer hits differently than I expected.]]></description>
			<content:encoded><![CDATA[<p>This translation actually makes the backprop diagram way clearer than the original English version. The way they explain the gradient flow in the pooling layer hits differently than I expected.</p>
]]></content:encoded>
		
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		<title>
		By: product copy generator		</title>
		<link>https://www.coder4.com/archives/5962#comment-22290</link>

		<dc:creator><![CDATA[product copy generator]]></dc:creator>
		<pubDate>Mon, 14 Sep 2026 09:04:50 +0000</pubDate>
		<guid isPermaLink="false">https://www.coder4.com/?p=5962#comment-22290</guid>

					<description><![CDATA[终于有人把池化层说清楚了，不用对着公式死磕。]]></description>
			<content:encoded><![CDATA[<p>终于有人把池化层说清楚了，不用对着公式死磕。</p>
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		<title>
		By: plinko clicker game		</title>
		<link>https://www.coder4.com/archives/5962#comment-22283</link>

		<dc:creator><![CDATA[plinko clicker game]]></dc:creator>
		<pubDate>Sun, 13 Sep 2026 19:45:47 +0000</pubDate>
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					<description><![CDATA[The sliding filter explanation is the part that actually clicked for me, especially seeing how the 3x3 kernel slides over the 5x5 matrix to generate that activation map. I still get why LeNet is such a good starting point though, even if the math part feels a bit dry.]]></description>
			<content:encoded><![CDATA[<p>The sliding filter explanation is the part that actually clicked for me, especially seeing how the 3x3 kernel slides over the 5x5 matrix to generate that activation map. I still get why LeNet is such a good starting point though, even if the math part feels a bit dry.</p>
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