1. Can you improve the single-shot multibox detection by improving the loss function? For example, replace L norm loss with smooth L1 norm loss for the predicted offsets. This loss function uses a square function around zero for smoothness, which is controlled by the hyperparameter o: f(2) = (ox)2/2, z| – 0.5/o2, otherwise if |r| < 1/o2 (13.7.1)

Computer Networking: A Top-Down Approach (7th Edition)
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Author:James Kurose, Keith Ross
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Chapter1: Computer Networks And The Internet
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1. Can you improve the single-shot multibox detection by improving the loss function? For
example, replace Lị norm loss with smooth L1 norm loss for the predicted offsets. This
loss function uses a square function around zero for smoothness, which is controlled by the
hyperparameter o:
if |r| < 1/o?
U2| - 0.5/o2, otherwise
f(1)
(13.7.1)
When a is very large, this loss is similar to the Li norm loss. When its value is smaller, the loss
function is smoother.
Transcribed Image Text:1. Can you improve the single-shot multibox detection by improving the loss function? For example, replace Lị norm loss with smooth L1 norm loss for the predicted offsets. This loss function uses a square function around zero for smoothness, which is controlled by the hyperparameter o: if |r| < 1/o? U2| - 0.5/o2, otherwise f(1) (13.7.1) When a is very large, this loss is similar to the Li norm loss. When its value is smaller, the loss function is smoother.
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