U-ASD Net: Supervised Crowd Counting Based on Semantic Segmentation and Adaptive Scenario Discovery

U-ASD Net: Supervised Crowd Counting Based on Semantic Segmentation and Adaptive Scenario Discovery

Crowd counting considers one of the most significant and challenging issues in computer vision and deep learning communities, whose applications are being utilized for various tasks. While this issue is well studied, it remains an open challenge to manage perspective distortions and scale variations...

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Bibliographic Details
Main Authors: Adel Hafeezallah, Ahlam Al-Dhamari, Syed Abd Rahman Abu-Bakar
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Computer vision
deep learning
crowd counting
density map estimation
U-Net
adaptive scenario discovery
Online Access:https://ieeexplore.ieee.org/document/9536723/

Internet

https://ieeexplore.ieee.org/document/9536723/

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