This is the best series I have watched on explanation of object detection algorithms. Also, your approach of asking fundamental questions like "Why in this case, a metric of evaluation can't be used as a loss function" and many more such questions you addressed were so insightful. Really grateful for the efforts you've put in here. Thank you. 🙏🙏
Thanks. Really helpful and easy to understand tutorial. you mentioned that this is used to measure similarity between boxes. Can you elaborate how this can be used with geospatial and image capture?
It is not about comparing the images rather the two bounding boxes in a given image. The metric is used in the field of object detection and is used to compare the ground truth box and the predicted box by the neural network.
This is the best series I have watched on explanation of object detection algorithms.
Also, your approach of asking fundamental questions like "Why in this case, a metric of evaluation can't be used as a loss function" and many more such questions you addressed were so insightful. Really grateful for the efforts you've put in here. Thank you. 🙏🙏
So, in-depth and with those visualization it is a grate learning experience
Binge watching your videos. Excellent content and excellent teaching. Thank you.
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We are okay with imperfections as long as they are useful to us ... great wisdom🙏
awesome explanation!
Great Video !! Thanks.
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Thanks. Really helpful and easy to understand tutorial. you mentioned that this is used to measure similarity between boxes. Can you elaborate how this can be used with geospatial and image capture?
I am not sure if I understand your question. Possible to elaborate and give an example?
@@KapilSachdeva Is it used for compring 2 images and checking the differences/similarity? I am actually after an example in real life.
It is not about comparing the images rather the two bounding boxes in a given image. The metric is used in the field of object detection and is used to compare the ground truth box and the predicted box by the neural network.
is the same understanding can also be put on semantic and instance segmentation ?
You can use the notion of overlap in segmentation as well.
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Sorry. Not sure I understand your comment.