give_me_the_truth
give_me_the_truth OP t1_ivdfyec wrote
Reply to comment by cmilkau in [D] Enforcing object order in object detection by give_me_the_truth
>History shows that it is usually better to keep learning as simple as possible and not force the NN to learn the way you think it would be best.
Got it. Any references you have off the top of your head?
give_me_the_truth OP t1_iv9rwop wrote
Reply to comment by Relevant-Number7428 in [D] Enforcing object order in object detection by give_me_the_truth
Understood. Thanks for the idea 👍
give_me_the_truth OP t1_iv9kyup wrote
Reply to comment by fnbr in [D] Enforcing object order in object detection by give_me_the_truth
It is like I know beforehand that object1 will always be on the left of object2. If network predicts object2 to left of object1 then I have to discard those predictions and I know it is incorrect. If I incorporate this constraint then I can get predictions that I am looking for.
give_me_the_truth OP t1_iv930k9 wrote
Reply to comment by seiqooq in [D] Enforcing object order in object detection by give_me_the_truth
it could mean predicted coordinates have condition: object1_x < object2_x and object2_y < object2_y i.e., both x and y coordinates of object1 < both x and y coordinates of object2
Submitted by give_me_the_truth t3_yni223 in MachineLearning
give_me_the_truth t1_isx6x1l wrote
Just to help me be aware about how one achieves good accuracy quickly: At a very high level what are the basic steps you followed to achieve 90% accuracy?
give_me_the_truth t1_ixcwr6u wrote
Reply to comment by BBAAQQDDD in [D] Simple Questions Thread by AutoModerator
It is not clear what is z.
However I think gradient descent can also be thought of as back propagation in its simplest sense where independent variable is updated based on change in dependent variable.