How does CNN doing bounding box regression and what do features and weights represent for?
0
$begingroup$
I knew that,in the house price logistical regression problem,the weights and features represent the "importance" of factor or coefficients of feature variables respectively,then minimize LSR loss can get the value of coefficients,and question are: 1,How does CNN doing bounding box regression? I actually did a lot of googling to find a intuitive explanation,but no lucky. 2,What do features and weights represent for in BBR? I think it couldn't be T,L,W,H,because these absolute values will vary a lot due to distance/scale and perspective difference,but the ratio of W/H is a reasonable feature (for me to understand) due to it is a relative value.
cnn
share
...