Submitted by somebodyenjoy t3_zc24rg in MachineLearning
somebodyenjoy OP t1_iyuz8tx wrote
Reply to comment by SeucheAchat9115 in [D] Best object detection architecture out there in terms of accuracy alone by somebodyenjoy
In this case, what would be the better option?
SeucheAchat9115 t1_iyuzb7c wrote
I guess yolov7 is a good choice, but depends on your institute be aware of the licenses of the code.
somebodyenjoy OP t1_iyv3jls wrote
What would be the accuracy of the brute-force approach, i.e. sliding window approach? Would the accuracy be better than all others?
SeucheAchat9115 t1_iyv5t91 wrote
Sliding window approches are „Conventional“ Image Processing techniques which are not comptitive anymore nowadays.
somebodyenjoy OP t1_iyv5zlq wrote
Maybe in terms of speed, but what about accuracy? Wouldn’t it make sense that a classifier going around the image would be more accurate? Is there any research or articles comparing the modern algorithms to sliding windows
SeucheAchat9115 t1_iyv631b wrote
Deep Learning Classifiers based on Convolutions also go around the whole image. And the sliding window approaches are not competitive anymore in terms of accuracy as well
somebodyenjoy OP t1_iyv79r7 wrote
I understand, I was asking if we use something like an alexnet and train it on a specific object, like a dog or not detector. Then make this detector go around the entire image in a brute-force manner, would that be more accurate than the object detector models right now
SeucheAchat9115 t1_iyv7fcl wrote
No, because the object detector can solve the problem in a single forward path. Todays deep learning based object detectors like Yolo or RCNN + Swin are very good choices for a detection task
somebodyenjoy OP t1_iyv8ila wrote
You mean to say they can do better in terms of accuracy even tho they detect in a single forward path?
SeucheAchat9115 t1_iyv8t0s wrote
Yes, because Deep Learning is way better than conventional Methods.
Flag_Red t1_iyvot70 wrote
He doesn't know.
killver t1_iyv1zfo wrote
EfficientDet if you care about license.
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