Yes, you can definitely change/modify the architecture. I have a course in modifying yolo architecture. It's for YOLOv8 actually, but it is similar to YOLO11 because YOLO11 is based on YOLOV8. You can search on Udemy
Thank you for the detailed explanation.. Quick question, what if I'm using Yolov11-cls for classifications will the overall architecture change? or only the head? Thank you!
@@rawanelabied6654 Based on the architecture file github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/models/11/yolo11-cls.yaml. The backbone for classification and detection is the same, but there is an additional C2PSA block. In classification there is no neck section, it goes directly to the Classify head section.
Heloo professor I'm currently working on my r Masters thesis What do you think is the best Yolo for detection of different varieties of a certain plant species The detection is by the leaf
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wow! great explanation of YOLOv11 architecture :) but I have one question, can you explore the limitation of using certain novel algorithm in YOLOv11 (e.g C3K2, C2PSA, etc)? because science is not only finding new way of doing things but also finding limitation of new algorithm and so far I haven't seen any discussion or paper that criticize YOLOv11
Thanks. That is a serious question. It needs a strong hypothesis and careful experiment to prove it. We have tried YOLO11 with several different cases and YOLO11 has several inaccuracies. You can check the video here: ua-cam.com/video/6Q81IXSiIEc/v-deo.html&pp=ygUHeW9sb3YxMQ%3D%3D . However we could not, with confident, say what contributes to these inaccuracies. We are still trying to find out.
@Dr.Priyanto.Hidayatullah I agree with you, we still need to do more research on this particular subject. Every model tries to outcompeting each other so they evolved so fast with new algorithm, new bugs, etc... one more question, with so many YOLO version out there, from your experience which YOLO version is the most "production ready"? because from what I learned from your past videos, the newest isn't always the best. Thanks for your answer
@@mohalem YOLO11 now is the inital release. So don't worry, I believe Ultralytics will improve it by time. As in YOLOv8. They improved it and released an updated versions several times until now the YOLOv8.3 (which is better than YOLOv8 initial release). As for now, I am not saying the others are not production ready, I personally would rather recommend YOLOv8.3.
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A great explanation! Thank You Dr. Priyanto, your explanation is so clear.
@@wahyuadinugroho_id you're welcome. Alhamdulillah
It is a very good explanation. I want to know that can I change the YOLO11 architecture.
Yes, you can definitely change/modify the architecture. I have a course in modifying yolo architecture. It's for YOLOv8 actually, but it is similar to YOLO11 because YOLO11 is based on YOLOV8. You can search on Udemy
Would you explain how archirecture changes for segmentation task?
@@natalia22777 I wish we could. We are in a hectic condition
sir good explanation, can u please provide this yolov11 diagram for proper understanding
Thank you for the detailed explanation.. Quick question, what if I'm using Yolov11-cls for classifications will the overall architecture change? or only the head? Thank you!
@@rawanelabied6654 Based on the architecture file github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/models/11/yolo11-cls.yaml. The backbone for classification and detection is the same, but there is an additional C2PSA block. In classification there is no neck section, it goes directly to the Classify head section.
Heloo professor
I'm currently working on my r
Masters thesis
What do you think is the best Yolo for detection of different varieties of a certain plant species
The detection is by the leaf
If your class is specific, then any model from YOLOv8 - YOLO11 is good.
Great breakdown of YOLO11 architecture
Thank you, alhamdulilah
Where can we a breakdown of the output structure? I wanto to extract keypoints and confidence score after running the model on an image
I am a little bit confused with the question. However, the output is at the Detect block
@@Dr.Priyanto.Hidayatullah can I message u privately somehow to discuss
@@rishiarjun9045 we can discuss here so that others can help me answer your questions/queries :)
excelent video, thanks to much, greatings from Santiago de Chile
@@camarastransporte you're welcome. Glad it was helpful
Could you explain YOLOv11-seg architecture?
@@HaVu-jb8cv that would be making another video 😬
Apakah ada harga promo untuk mengikuti kelasnya di Udemy Prof?
To get DISCOUNT, please click this link. Caution: The discount is time limited! Enroll asap.
www.udemy.com/course/yolo-masterclass-deep-learning-computer-vision-course/?couponCode=BLACK_FRIDAY
@@Dr.Priyanto.Hidayatullah thank you, prof.
@@fahricok2790 you're welcome
why there is no information about Detection block parts?
We want to present in different forms
wow! great explanation of YOLOv11 architecture :) but I have one question, can you explore the limitation of using certain novel algorithm in YOLOv11 (e.g C3K2, C2PSA, etc)? because science is not only finding new way of doing things but also finding limitation of new algorithm and so far I haven't seen any discussion or paper that criticize YOLOv11
Thanks.
That is a serious question. It needs a strong hypothesis and careful experiment to prove it. We have tried YOLO11 with several different cases and YOLO11 has several inaccuracies. You can check the video here: ua-cam.com/video/6Q81IXSiIEc/v-deo.html&pp=ygUHeW9sb3YxMQ%3D%3D . However we could not, with confident, say what contributes to these inaccuracies. We are still trying to find out.
@Dr.Priyanto.Hidayatullah I agree with you, we still need to do more research on this particular subject. Every model tries to outcompeting each other so they evolved so fast with new algorithm, new bugs, etc... one more question, with so many YOLO version out there, from your experience which YOLO version is the most "production ready"? because from what I learned from your past videos, the newest isn't always the best. Thanks for your answer
@@mohalem YOLO11 now is the inital release. So don't worry, I believe Ultralytics will improve it by time. As in YOLOv8. They improved it and released an updated versions several times until now the YOLOv8.3 (which is better than YOLOv8 initial release).
As for now, I am not saying the others are not production ready, I personally would rather recommend YOLOv8.3.
@Dr.Priyanto.Hidayatullah thank you for your consideration
Can you make in Indonesia version?
Not at the moment. We are now doing several tasks that need high concentration.