Estimate the size of crowd by KERAS and CNN

Please use this identifier to cite or link to this item: http://tainguyenso.dut.udn.vn/handle/DUT/4149

DC Field	Value	Language
dc.contributor.advisor	Nguyen, Thi Anh Thu, Dr
dc.contributor.author	Thai, Duy Dat
dc.date.accessioned	2024-11-06T05:23:44Z	-
dc.date.available	2024-11-06T05:23:44Z	-
dc.date.issued	2022
dc.identifier.uri	http://tainguyenso.dut.udn.vn/handle/DUT/4149	-
dc.description	DA.FA.22.082 ; 48 p.	vi
dc.description.abstract	Currently, estimate the size of crowd is very necessary due to the complicated situation of the epidemic. There are many methods of crowd estimation currently proposed such as the method based on the HOG algorithm combined with SVM, the regression-based approach (using Fourier and SIFT analysis), the method using the MCNN, but the mean absolute error (MAE) and mean square error (MSE) are still high. In this report, I have estimated the number of people in the crowd using CSRnet which is a convolutional neural network with ten hidden layers, and the data after each estimate is stored on thingspeak.com	vi
dc.language.iso	en	vi
dc.publisher	Trường Đại học Bách khoa - Đại học Đà Nẵng	vi
dc.subject	CSRnet	vi
dc.subject	Deep learning	vi
dc.subject	Neuron network	vi
dc.title	Estimate the size of crowd by KERAS and CNN	vi
dc.type	Đồ án	vi
item.cerifentitytype	Publications	-
item.openairetype	Đồ án	-
item.grantfulltext	restricted	-
item.openairecristype	http://purl.org/coar/resource_type/c_18cf	-
item.fulltext	Có toàn văn	-
item.languageiso639-1	en	-
Appears in Collections:	DA.Tin học công nghiệp

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