Update README.md with YOLO11 section (#13374)

* Update README with YOLO11

* Update README with YOLO11

---------

Co-authored-by: UltralyticsAssistant <web@ultralytics.com>

README.zh-CN.md

@@ -41,21 +41,21 @@ YOLOv5 🚀 是世界上最受欢迎的视觉 AI，代表<a href="https://www.ul
 </div>
 </div>
 
-## <div align="center">YOLOv8 🚀 新品</div>
+## <div align="center">YOLO11 🚀 全新发布</div>
 
-我们很高兴宣布 Ultralytics YOLOv8 🚀 的发布，这是我们新推出的领先水平、最先进的（SOTA）模型，发布于 **[https://github.com/ultralytics/ultralytics](https://github.com/ultralytics/ultralytics)**。 YOLOv8 旨在快速、准确且易于使用，使其成为广泛的物体检测、图像分割和图像分类任务的极佳选择。
+我们很高兴宣布推出 Ultralytics YOLO11 🚀，这是我们最先进视觉模型的最新进展！现已在 **[GitHub](https://github.com/ultralytics/ultralytics)** 上发布。YOLO11 在速度、精度和易用性方面进一步提升，无论是处理目标检测、图像分割还是图像分类任务，YOLO11 都具备出色的性能和多功能性，助您在各种应用中脱颖而出。
 
-请查看 [YOLOv8 文档](https://docs.ultralytics.com/)了解详细信息，并开始使用：
+立即开始，解锁 YOLO11 的全部潜力！访问 [Ultralytics 文档](https://docs.ultralytics.com/) 获取全面的指南和资源：
 
 [![PyPI 版本](https://badge.fury.io/py/ultralytics.svg)](https://badge.fury.io/py/ultralytics) [![下载量](https://static.pepy.tech/badge/ultralytics)](https://pepy.tech/project/ultralytics)
 
-```commandline
+```bash
 pip install ultralytics
 ```
 
 <div align="center">
   <a href="https://www.ultralytics.com/yolo" target="_blank">
-  <img width="100%" src="https://raw.githubusercontent.com/ultralytics/assets/main/yolov8/yolo-comparison-plots.png"></a>
+  <img width="100%" src="https://raw.githubusercontent.com/ultralytics/assets/refs/heads/main/yolo/performance-comparison.png"></a>
 </div>
 
 ## <div align="center">文档</div>
@@ -139,22 +139,22 @@ python train.py --data coco.yaml --epochs 300 --weights '' --cfg yolov5n.yaml  -
 <details open>
 <summary>教程</summary>
 
-- [训练自定义数据](https://docs.ultralytics.com/yolov5/tutorials/train_custom_data/) 🚀 推荐
-- [获得最佳训练结果的技巧](https://docs.ultralytics.com/guides/model-training-tips/) ☘️
+- [自定义数据训练](https://docs.ultralytics.com/yolov5/tutorials/train_custom_data/) 🚀 **推荐**
+- [最佳训练效果的提示](https://docs.ultralytics.com/guides/model-training-tips/) ☘️
 - [多GPU训练](https://docs.ultralytics.com/yolov5/tutorials/multi_gpu_training/)
-- [PyTorch Hub](https://docs.ultralytics.com/yolov5/tutorials/pytorch_hub_model_loading/) 🌟 新
-- [TFLite，ONNX，CoreML，TensorRT导出](https://docs.ultralytics.com/yolov5/tutorials/model_export/) 🚀
-- [NVIDIA Jetson平台部署](https://docs.ultralytics.com/yolov5/tutorials/running_on_jetson_nano/) 🌟 新
+- [PyTorch Hub](https://docs.ultralytics.com/yolov5/tutorials/pytorch_hub_model_loading/) 🌟 **全新**
+- [TFLite, ONNX, CoreML, TensorRT 导出](https://docs.ultralytics.com/yolov5/tutorials/model_export/) 🚀
+- [NVIDIA Jetson 平台部署](https://docs.ultralytics.com/yolov5/tutorials/running_on_jetson_nano/) 🌟 **全新**
 - [测试时增强 (TTA)](https://docs.ultralytics.com/yolov5/tutorials/test_time_augmentation/)
 - [模型集成](https://docs.ultralytics.com/yolov5/tutorials/model_ensembling/)
-- [模型剪枝/稀疏](https://docs.ultralytics.com/yolov5/tutorials/model_pruning_and_sparsity/)
+- [模型剪枝/稀疏化](https://docs.ultralytics.com/yolov5/tutorials/model_pruning_and_sparsity/)
 - [超参数进化](https://docs.ultralytics.com/yolov5/tutorials/hyperparameter_evolution/)
 - [冻结层的迁移学习](https://docs.ultralytics.com/yolov5/tutorials/transfer_learning_with_frozen_layers/)
-- [架构概述](https://docs.ultralytics.com/yolov5/tutorials/architecture_description/) 🌟 新
-- [Roboflow用于数据集、标注和主动学习](https://docs.ultralytics.com/yolov5/tutorials/roboflow_datasets_integration/)
-- [ClearML日志记录](https://docs.ultralytics.com/yolov5/tutorials/clearml_logging_integration/) 🌟 新
-- [使用Neural Magic的Deepsparse的YOLOv5](https://docs.ultralytics.com/yolov5/tutorials/neural_magic_pruning_quantization/) 🌟 新
-- [Comet日志记录](https://docs.ultralytics.com/yolov5/tutorials/comet_logging_integration/) 🌟 新
+- [架构概述](https://docs.ultralytics.com/yolov5/tutorials/architecture_description/) 🌟 **全新**
+- [使用 Ultralytics HUB 进行 YOLO 训练和部署](https://www.ultralytics.com/hub) 🚀 **推荐**
+- [ClearML 日志记录](https://docs.ultralytics.com/yolov5/tutorials/clearml_logging_integration/)
+- [与 Neural Magic 的 Deepsparse 集成的 YOLOv5](https://docs.ultralytics.com/yolov5/tutorials/neural_magic_pruning_quantization/)
+- [Comet 日志记录](https://docs.ultralytics.com/yolov5/tutorials/comet_logging_integration/) 🌟 **全新**
 
 </details>