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feat: 完整中文翻译 maths-cs-ai-compendium（数学·计算机科学·AI 知识大全）

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翻译自英文原版 maths-cs-ai-compendium，共 20 章全部完成。

第01章 向量 | 第02章 矩阵 | 第03章 微积分
第04章 统计学 | 第05章 概率论 | 第06章 机器学习
第07章 计算语言学 | 第08章 计算机视觉 | 第09章 音频与语音
第10章 多模态学习 | 第11章 自主系统 | 第12章 图神经网络
第13章 计算与操作系统 | 第14章 数据结构与算法
第15章 生产级软件工程 | 第16章 SIMD与GPU编程
第17章 AI推理 | 第18章 ML系统设计
第19章 应用人工智能 | 第20章 前沿人工智能

翻译说明：
- 所有数学公式 $...$ / $$...$$、代码块、图片引用完整保留
- mkdocs.yml 配置中文导航 + language: zh
- README.md 已翻译为中文（兼 docs/index.md）
- docs/ 目录包含指向各章文件的 symlink
- 约 29,000 行中文内容，排除 .cache/ 构建缓存
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flykhan
2026-05-03 10:23:20 +08:00
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<marker id="fcos-arrow" markerWidth="7" markerHeight="5" refX="7" refY="2.5" orient="auto">
<polygon points="0 0, 7 2.5, 0 5" fill="#555"/>
</marker>
</defs>
<text x="350" y="22" fill="#333" font-size="14" font-weight="bold" text-anchor="middle">FCOS: Anchor-Free Per-Pixel Detection</text>
<!-- Feature map grid -->
<text x="130" y="48" fill="#666" font-size="11" text-anchor="middle">Feature Map</text>
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<line x1="30" y1="175" x2="230" y2="175" stroke="#ddd" stroke-width="0.5"/>
<!-- Ground truth bounding box -->
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<text x="115" y="72" fill="#3498db" font-size="8" text-anchor="middle" font-weight="bold">Ground Truth Box</text>
<!-- A point inside the box with distances shown -->
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<!-- Distance arrows from point to box edges -->
<!-- Left (l) -->
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<text x="68" y="110" fill="#e74c3c" font-size="8" text-anchor="middle" font-weight="bold">l</text>
<!-- Top (t) -->
<line x1="90" y1="113" x2="90" y2="82" stroke="#27ae60" stroke-width="1.5" marker-end="url(#fcos-arrow)"/>
<text x="97" y="95" fill="#27ae60" font-size="8" text-anchor="start" font-weight="bold">t</text>
<!-- Right (r) -->
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<!-- Arrow to outputs -->
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<!-- Classification -->
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<text x="375" y="73" fill="#3498db" font-size="10" text-anchor="middle" font-weight="bold">Classification Head</text>
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<text x="375" y="123" fill="#e74c3c" font-size="10" text-anchor="middle" font-weight="bold">Regression Head</text>
<text x="375" y="138" fill="#e74c3c" font-size="8" text-anchor="middle">(l, t, r, b) distances per pixel</text>
<!-- Centerness -->
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<text x="375" y="173" fill="#27ae60" font-size="10" text-anchor="middle" font-weight="bold">Centerness Head</text>
<text x="375" y="188" fill="#27ae60" font-size="8" text-anchor="middle">suppresses low-quality detections</text>
<!-- Centerness formula -->
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<text x="585" y="75" fill="#333" font-size="9" text-anchor="middle" font-weight="bold">Centerness score:</text>
<text x="585" y="92" fill="#333" font-size="9" text-anchor="middle">√(min(l,r)/max(l,r))</text>
<text x="585" y="108" fill="#333" font-size="9" text-anchor="middle">× √(min(t,b)/max(t,b))</text>
<!-- FPN note -->
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<text x="585" y="150" fill="#9b59b6" font-size="9" text-anchor="middle" font-weight="bold">Multi-scale with FPN:</text>
<text x="585" y="168" fill="#666" font-size="9" text-anchor="middle">Small objects → high-res levels</text>
<text x="585" y="183" fill="#666" font-size="9" text-anchor="middle">Large objects → low-res levels</text>
<!-- Bottom note -->
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<text x="350" y="235" fill="#333" font-size="9" text-anchor="middle">No anchors needed. Every feature map location inside a ground truth box is a positive training sample.</text>
<text x="350" y="250" fill="#666" font-size="9" text-anchor="middle">Centerness down-weights predictions far from object centres, improving precision without NMS changes.</text>
</svg>
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