Okay, I need to create a Wikipedia-style document about Convolutional Neural Networks (CNNs) under the categories of Technology > Artificial Intelligence > Machine Learning. Let me start by understanding the requirements.

First, the structure: H1 for the title, an overview section, several H2 and H3 sections, and maybe references or related documents. The content needs to be accurate, objective, detailed enough, easy to read, and use technical terms with explanations. Also, markdown formatting with proper headings, lists, tables, code blocks if needed, and at least 800 characters.

Starting with the title: "컨볼루셔널 네트워크" as given. Then an introduction that explains what CNNs are, their purpose, and maybe a brief history. Next sections could be architecture, key components like convolutional layers, pooling, activation functions, fully connected layers. Maybe applications, advantages, challenges, and future directions.

I should make sure each section has enough detail. For example, in the architecture section, explain each layer type with H3 headings. Use bullet points for components of a convolutional layer. Maybe include a table comparing different types of pooling. Also, mention common activation functions like ReLU.

Need to check if I have all required parts: introduction, sections with H2 and H3, references. Let me think about the flow. Introduction sets the stage, then architecture details, followed by components, applications, pros/cons, and future trends.

I should avoid being too technical without explanations. For example, when mentioning "kernel" or "feature maps," briefly explain them. Also, include examples of real-world applications like image recognition, object detection to make it relatable.

Check for markdown formatting: use # for H1, ## for H2, ### for H3. Use bold for key terms. Maybe a code block example with PyTorch or TensorFlow? But the user didn't specify code examples, so maybe just mention frameworks without code.

Need to ensure the document is over 800 characters. Let me count: each section should have enough content. Introduction might be 150 words, architecture 200, components 300, applications 150, advantages and challenges 100, future directions 100. That's around 900.

Also, include references or related documents at the end. Maybe list some key papers like LeNet, AlexNet, or frameworks like TensorFlow/PyTorch.

Wait, the user mentioned "필요시 참고 자료나 관련 문서 섹션" so I should add a section for that. Maybe under each H2 or as a separate H2. Let me structure it as a "참고 자료" section at the end.

Check for technical terms: convolutional layer, pooling, activation functions, feature maps, etc. Make sure to explain them briefly. For example, in the convolutional layer section, explain what a kernel is and how it slides over the input.

Avoid markdown syntax errors. Use proper headings, lists with hyphens, tables if needed. Maybe a table comparing different CNN architectures like LeNet, AlexNet, VGG, ResNet.

Also, ensure that each H2 section has at least one H3 sub-section. For example, under "핵심 구성 요소", have H3 for convolutional layers, pooling layers, etc.

Double-check the Korean terms: "컨볼루셔널 네트워크" is correct. Use proper terminology in Korean, like "畳み込み층" (convolutional layer), "풀링 층" (pooling layer).

Make sure the document flows logically and covers all aspects of CNNs as per the categories given. Avoid redundancy but ensure thorough coverage.