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"You Only Look Once", a Deep Learning-based object recognition algorithm available in several different software implementations.
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Yolo v1 - what is the purpose of the confidence Ci?
YOLO v1 model predicts the confidence score $\hat{C_i}$ but I am not clear with the purpose of $\hat{C_i}$.
Definition of the confidence score in the YOLO v1 paper. … This is why I wonder if $\hat{C_i}$ is essential in YOLO v1.
The question is what role does $\hat{C_i}$ play and if we really need it? …
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Accepted
Yolo v1 - what is the purpose of the confidence Ci?
I think this may not be explained in detail in the paper, but found a good article YOLO — ‘You only look once’ for Object Detection explained. …
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YOLO loss function width and height component explanation
YOLOv1 from Scratch explains as below. It also explains other considerations made in the loss function design.
Lets say we have a very large bounding box and we take those subtracts and squared, that …
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How to "use" Yolo Loss Function
It explains other considerations e.g. questioned in YOLO loss function width and height component explanation. …
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What is the need of multiple Bounding Boxes per grid cell in YOLO v1?
This steps are well explained in YOLO — ‘You only look once’ for Object Detection explained. … However, because YOLO puts the importance on the real-time detection speed, B is set to 2, in my understanding. …
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yolo cost function
if we have negative values for the width and height
As in the original paper, the bounding box size is normalised between 0 and 1, hence will not be negative.