/en/tags/object-detection/Recent content in Object Detection on Mi&Bee BlogHugo -- gohugo.ioen蓝宝石的傻话Tue, 05 May 2026 00:00:00 +0000/en/posts/aihelper/yolo-getting-started/Tue, 05 May 2026 00:00:00 +0000/en/posts/aihelper/yolo-getting-started/<h2 id="learning-path-and-version-selection-guide">Learning Path and Version Selection Guide</h2> <h3 id="version-selection-guide">Version Selection Guide</h3> <table> <thead> <tr> <th>Version</th> <th>Release Date</th> <th>Development Team</th> <th>Use Cases</th> <th>Recommendation Index</th> </tr> </thead> <tbody> <tr> <td><strong>YOLO26</strong></td> <td>2026.01</td> <td>Ultralytics Official</td> <td>Edge deployment, CPU inference, industrial applications</td> <td>⭐⭐⭐⭐⭐</td> </tr> <tr> <td><strong>YOLOv8</strong></td> <td>2023.01</td> <td>Ultralytics Official</td> <td>Beginner learning, complete ecosystem, general scenarios</td> <td>⭐⭐⭐⭐⭐</td> </tr> <tr> <td><strong>YOLO11</strong></td> <td>2024.09</td> <td>Ultralytics Official</td> <td>Efficiency optimization, lightweight deployment</td> <td>⭐⭐⭐⭐</td> </tr> <tr> <td><strong>YOLOv10</strong></td> <td>2024.05</td> <td>Tsinghua University</td> <td>Research exploration, NMS-free end-to-end</td> <td>⭐⭐⭐⭐</td> </tr> <tr> <td><strong>YOLOv9</strong></td> <td>2024.01</td> <td>National Taiwan University</td> <td>High precision, small object detection</td> <td>⭐⭐⭐⭐</td> </tr> <tr> <td><strong>YOLOv12</strong></td> <td>2025.02</td> <td>Buffalo University + Chinese Academy of Sciences</td> <td>Attention mechanism research</td> <td>⭐⭐⭐</td> </tr> </tbody> </table> <h3 id="learning-path-recommendations">Learning Path Recommendations</h3> <ol> <li><strong>Beginner Stage (1-2 weeks)</strong>: Start with <strong>YOLOv8</strong>, master basic concepts and API usage</li> <li><strong>Intermediate Stage (2-3 weeks)</strong>: Learn custom dataset training, parameter tuning and optimization</li> <li><strong>Advanced Stage (2-3 weeks)</strong>: Learn model deployment, engineering implementation</li> <li><strong>Research Stage (ongoing)</strong>: Explore new features in YOLO11, YOLO26, YOLOv9/v10/v12</li> </ol> <h2 id="complete-yolo-development-history-timeline">Complete YOLO Development History Timeline</h2> <table> <thead> <tr> <th>Version</th> <th>Release Date</th> <th>Core Innovation</th> <th>Milestone Significance</th> </tr> </thead> <tbody> <tr> <td>YOLOv1</td> <td>2015.06</td> <td>Pioneer single-stage detection</td> <td>Foundation for real-time detection</td> </tr> <tr> <td>YOLOv2</td> <td>2016.12</td> <td>Batch Normalization, Anchor</td> <td>Dual improvement in accuracy and speed</td> </tr> <tr> <td>YOLOv3</td> <td>2018.04</td> <td>Multi-scale detection, residual networks</td> <td>Industry standard</td> </tr> <tr> <td>YOLOv4</td> <td>2020.04</td> <td>CSPDarknet, Mosaic</td> <td>Peak of engineering implementation</td> </tr> <tr> <td>YOLOv5</td> <td>2020.06</td> <td>PyTorch framework, user-friendly</td> <td>Highest adoption rate</td> </tr> <tr> <td>YOLOv7</td> <td>2022.07</td> <td>E-ELAN, reparameterization</td> <td>Balance between speed and accuracy</td> </tr> <tr> <td><strong>YOLOv8</strong></td> <td>2023.01</td> <td>C2f, Anchor-Free, unified framework</td> <td>Ultralytics unified ecosystem</td> </tr> <tr> <td><strong>YOLOv9</strong></td> <td>2024.01</td> <td>GELAN, PGI programmable gradient</td> <td>Training efficiency revolution</td> </tr> <tr> <td><strong>YOLOv10</strong></td> <td>2024.05</td> <td>NMS-free, efficiency-precision tradeoff</td> <td>End-to-end detection</td> </tr> <tr> <td><strong>YOLO11</strong></td> <td>2024.09</td> <td>Architecture optimization, parameter reduction</td> <td>Efficiency optimized version</td> </tr> <tr> <td><strong>YOLOv12</strong></td> <td>2025.02</td> <td>Area Attention mechanism</td> <td>Attention architecture</td> </tr> <tr> <td><strong>YOLO26</strong></td> <td>2026.01</td> <td>DFL-free, NMS-free, 43% CPU optimization</td> <td>Edge computing new standard</td> </tr> </tbody> </table> <h2 id="core-principles-and-version-comparison">Core Principles and Version Comparison</h2> <h3 id="ultralytics-official-main-line-versions">Ultralytics Official Main Line Versions</h3> <p><strong>YOLOv8 Core Features:</strong></p>