Learning Models in Crowd Analysis: A Review
Crowd detection and counting are important tasks in several applications of crowd analysis
including traffic management, public safety and event planning. Automatic crowd counting …
including traffic management, public safety and event planning. Automatic crowd counting …
Dilated high-resolution network driven RGB-T multi-modal crowd counting
Crowd counting aims to estimate the number of pedestrians in a scene. However, the
problems of insufficient illumination and large-scale variation affect the accuracy of crowd …
problems of insufficient illumination and large-scale variation affect the accuracy of crowd …
Assessing Crowd Counting Methods: A Comparison Study of MaskR-CNN
The primary goal of crowd counting is to ascertain the total number of individuals in a
congested area, and the expanding field of computer vision facilitates the analysis of crowd …
congested area, and the expanding field of computer vision facilitates the analysis of crowd …
Assessing Crowd Counting Methods: A Comparison Study of MaskR-CNN with ResNet 50 and Convolution Neural Network
Crowd counting is the task of estimating the number of individuals in a crowd that has
gained significant attention in computer vision research due to its diverse applications in …
gained significant attention in computer vision research due to its diverse applications in …
[PDF][PDF] Research Progress of Encoder-Decoder Network in Image Fusion
X Zhang, Q Cheng, Q Li, H Lu - papers.ssrn.com
TImage fusion is a research hotspot in the field of computer vision, which obtains
complementary information from the different modal images and then presents it in a …
complementary information from the different modal images and then presents it in a …