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Logistic Classifier The logistic classifier is similar to equation of the plane. W is weight vector, X is input vector and y is output... -
* Introduction - The solution shows panorama image from multi images. The panorama images is processing by real-time stitching algorithm... -
This is data acquisition source code of LMS511(SICK co.) Source code is made by MFC(vs 2008). The sensor is communicated by TCP/IP. ... -
As you can see in the following video, I created a class that stitching n cameras in real time. https://www.youtube.com/user/feelmare/sear...
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I use MOG2 algorithm to background subtraction. The process is resize to small for more fast processing to blur for avoid noise affectio...
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In past, I wrote an articel about YUV 444, 422, 411 introduction and yuv rgb converting example code. refer to this page -> http://feel...
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Complete Tutorial: LabelMe with Login System and Dataset Management This guide provides step-by-step instructions for setting up LabelMe wit...
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source code ... const int ledPin = 13; const int knockSensor = A0; const int threshold = 100; int sensorReading = 0; int led... -
Dear Jihad anwar Here is source code you asking. I don't remember equation about particle filter well now. But source code is ...
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Calculate overlap percent between two rectangle It is not difficult, we just use bit operator : &, | for more detail informati...
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ReplyDeleteThis one is better than "More stringent pedestrian detection by Deep learning verification" and "More stringent pedestrian detection by HOG verification". Do you use OpenCV to achieve such result?
ReplyDeleteDetecting pedestrian using Deep learning is recorded high rate false positive, but not sensitive variable pedestrian pose. and processing speed is not good.
DeleteHog is fast, but to detect typical appearance when training data pose.
So, I can not say yet, which way is better..
Thank you.
can you share this source code! Thank you
ReplyDelete