@@ -311,7 +311,7 @@ The comparison between COCO mAP and FPS on Qualcomm Snapdragon 865 processor of
311311| :---------- | :------------------:| :-----------------------------:| :-------------------------------------------------------:| :----------------------------------------------------------------------------------------:| 
312312|  PP-YOLOE+_ s |  43.9        |  333.3                     |  [ link] ( configs/ppyoloe/ppyoloe_plus_crn_s_80e_coco.yml )      |  [ download] ( https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_s_80e_coco.pdparams )       | 
313313|  PP-YOLOE+_ m |  50.0        |  208.3                     |  [ link] ( configs/ppyoloe/ppyoloe_plus_crn_m_80e_coco.yml )      |  [ download] ( https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_m_80e_coco.pdparams )      | 
314- |  PP-YOLOE+_ l |  53.3        |  149.2                     |  [ link] ( configs/ppyoloe/ppyoloe_plus_crn_l_80e_coco.yml )  |  [ download] ( https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_m_80e_coco .pdparams )  | 
314+ |  PP-YOLOE+_ l |  53.3        |  149.2                     |  [ link] ( configs/ppyoloe/ppyoloe_plus_crn_l_80e_coco.yml )  |  [ download] ( https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_l_80e_coco .pdparams )  | 
315315|  PP-YOLOE+_ x |  54.9        |  95.2                      |  [ link] ( configs/ppyoloe/ppyoloe_plus_crn_x_80e_coco.yml )  |  [ download] ( https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_x_80e_coco.pdparams )  | 
316316
317317#### PP-PicoDet series Recommended scenarios: Mobile chips and x86 CPU devices, such as ARM CPU(RK3399, Raspberry Pi) and NPU(BITMAIN)  
@@ -470,20 +470,21 @@ Please refer to [docs](deploy/pipeline/README_en.md) for details.
470470-  ** [ Academic exchange]  2022.9.27 [ YOLO Vision Event] ( https://www.youtube.com/playlist?list=PL1FZnkj4ad1NHVC7CMc3pjSQ-JRK-Ev6O ) :**  As the first YOLO-themed event, PaddleDetection was invited to communicate with the experts in the field of Computer Vision around the world.
471471
472472### [ Industrial tutorial examples] ( ./industrial_tutorial/README.md )  
473+ 
474+ -  [ Rotated object detection based on PP-YOLOE-R] ( https://aistudio.baidu.com/aistudio/projectdetail/5058293 ) 
475+ 
476+ -  [ Aerial image detection based on PP-YOLOE-SOD] ( https://aistudio.baidu.com/aistudio/projectdetail/5036782 ) 
477+ 
473478-  [ Fall down recognition based on PP-Human v2] ( https://aistudio.baidu.com/aistudio/projectdetail/4606001 ) 
474479
475480-  [ Intelligent fitness recognition based on PP-TinyPose Plus] ( https://aistudio.baidu.com/aistudio/projectdetail/4385813 ) 
476481
477482-  [ Road litter detection based on PP-PicoDet Plus] ( https://aistudio.baidu.com/aistudio/projectdetail/3561097 ) 
478483
479- -  [ Communication tower detection based on PP-PicoDet and deployment on Android] ( https://aistudio.baidu.com/aistudio/projectdetail/3561097 ) 
480- 
481484-  [ Visitor flow statistics based on FairMOT] ( https://aistudio.baidu.com/aistudio/projectdetail/2421822 ) 
482485
483486-  [ Guest analysis based on PP-Human] ( https://aistudio.baidu.com/aistudio/projectdetail/4537344 ) 
484487
485- -  [ Fight recognition based on video classification] ( https://aistudio.baidu.com/aistudio/projectdetail/4512242 ) 
486- 
487488-  [ More examples] ( ./industrial_tutorial/README.md ) 
488489
489490## <img  title =" "  src =" https://user-images.githubusercontent.com/48054808/157836473-1cf451fa-f01f-4148-ba68-b6d06d5da2f9.png "  alt =" "  width =" 20 " > Applications  
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