可視化 AI 系統、神經網路架構和技術工作流對於機器學習論文、簡報和文件至關重要。本指南介紹了 30 個來自真實 AI 研究項目的成熟提示詞(prompts),幫助您為出版物創建專業的圖表。
你將學到:
- 神經網路架構可視化提示詞
- 演算法機制和工作流圖表
- 數據處理流水線插圖
- 系統整合與部署圖表
1. 神經網路架構圖
1.1 卷積神經網路
提示詞:詳細的 CNN 架構
I need to generate a detailed schematic diagram of a convolutional neural network
architecture. The generated diagram should clearly show:
- Input layer with image dimensions (e.g., 224×224×3)
- Multiple convolutional layers with filter sizes and feature map dimensions
- Pooling layers (max pooling) with stride annotations
- Fully connected layers with neuron counts
- Output layer with classification probabilities
Use a horizontal left-to-right flow with consistent color coding for each layer type.
1.2 演算法機制圖
提示詞:知識圖譜演算法工作流
Generate an image: Core visual theme and style.
Theme: algorithm mechanism diagram, technical workflow, abstract knowledge
representation. Show the pipeline from raw data input through entity extraction,
relationship mining, knowledge graph construction, to final reasoning output.
Include intermediate representations and transformation arrows with labels.
2. 技術系統架構
2.1 模擬與驗證平台
提示詞:數位模擬平台架構
Please create a technical architecture diagram for a full digital simulation
and verification platform for civil aircraft systems. Include:
- Data acquisition layer (sensors, flight data)
- Simulation engine layer (physics models, aerodynamics)
- Verification and validation modules
- User interface and visualization components
- Integration with external systems (CAD, CFD)
Use a layered architecture style with clear module boundaries.
2.2 控制系統
提示詞:自主控制系統架構
Please draw a technical architecture diagram of a multi-source disturbance
automatic takeoff and landing control system. Show:
- Sensor fusion module (IMU, GPS, vision)
- State estimation and prediction
- Control law computation
- Actuator command generation
- Feedback loops with disturbance rejection
Label all signals and processing blocks with technical terminology.
3. 數據處理流水線
3.1 機器學習工作流
提示詞:數據分析流水線
Data Loading:
Initially, the competition data CSV file is loaded into a DataFrame using pandas.
Create a workflow diagram showing:
1. Data ingestion and validation
2. Feature engineering and preprocessing
3. Model training with cross-validation
4. Hyperparameter optimization
5. Model evaluation and selection
6. Prediction and submission generation
Include data flow arrows and intermediate dataset shapes.
3.2 製造業檢測系統
提示詞:AI 驅動的檢測架構
Abstract: Modern manufacturing inspection relies on complex measurements due to
advanced production processes and intricate product designs. Create a system
architecture diagram showing:
- Image acquisition subsystem (cameras, lighting)
- AI inference engine (defect detection models)
- Quality decision module
- Integration with manufacturing execution system (MES)
- Real-time dashboard and alerting
Use industrial automation visual style with equipment icons.
4. 研究框架圖
4.1 AI 研究願景
提示詞:研究任務組織
This document outlines the research vision of CRAFT-AI, proposing nine research
tasks organized within four primary research areas. Create a hierarchical diagram
showing:
- Core research pillars (Foundation Models, Reasoning, Alignment, Applications)
- Individual research tasks under each pillar
- Cross-cutting themes and dependencies
- Timeline or phase indicators if applicable
Use academic poster style with clean typography.
5. AI 架構圖提示詞撰寫技巧
應包含的關鍵要素
| 圖表類型 | 核心組成部分 |
|---|---|
| 神經網路 | 層類型、維度、激活函數、數據流向 |
| 系統架構 | 模組、介面、數據流、外部整合 |
| 工作流 | 步驟、決策點、數據轉換、時序 |
| 演算法 | 輸入/輸出、處理階段、數學運算 |
最佳實踐
- 指定佈局方向:例如「由左至右」、「由上至下」或「分層佈局」。
- 包含維度資訊:例如層大小、數據形狀、時間標註。
- 使用技術術語:確保與您論文中的命名法一致。
- 要求一致的風格:指定配色方案、圖示風格和字體選擇。
開始創建您的 AI 架構圖
使用 Scidraw AI 的 AI 插圖工具嘗試這些提示詞:
- AI 架構圖產生器 — AI 建立神經網路與系統架構圖
- 創建您的圖表 →
- 瀏覽 AI 系統範例 →



