Deep Dilated Convolutional Neural Network for Crowd Density Image Classification with Dataset Augmentation for Hajj Pilgrimage

Deep Dilated Convolutional Neural Network for Crowd Density Image Classification with Dataset Augmentation for Hajj Pilgrimage

Almost two million Muslim pilgrims from all around the globe visit Mecca each year to conduct Hajj. Each year, the number of pilgrims grows, creating worries about how to handle such large crowds and avoid unpleasant accidents or crowd congestion catastrophes. In this paper, we introduced deep Hajj...

Full description

Bibliographic Details
Main Authors: Abdullah, J. (Author), Abdullah, N. (Author), Al Farid, F. (Author), Bhuiyan, R. (Author), Hashim, N. (Author), Mohd Isa, W.N (Author), Uddin, J. (Author)
Format: Article
Language:English
Published: MDPI 2022
Subjects:
Classification (of information)
Convolution
Convolutional neural network
Convolutional neural networks
Crowd density
crowd density classification
Crowd density classification
deep augmentation
Deep augmentation
Deep neural networks
Density classifications
Density images
Disaster prevention
FCNN
Hajj-crowd dataset
Hajj-Crowd dataset
Image classification
Images classification
Mathematical morphology
morphological operation
Morphological operations
Security systems
Online Access:View Fulltext in Publisher

Internet

View Fulltext in Publisher

Similar Items