U-ASD Net: supervised crowd counting based on semantic segmentation and adaptive scenario discovery

• Main Authors: Hafeezallah, Adel, Al-Dhamari, Ahlam, Abu-Bakar, Syed Abd. Rahman
• Format: Article
• Language: English
• Published: Institute of Electrical and Electronics Engineers Inc. 2021
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.utm.my/id/eprint/93961/1/SyedAbdRahman2021_UASDNetSupervisedCrowdCounting.pdf; http://eprints.utm.my/id/eprint/93961/; http://dx.doi.org/10.1109/ACCESS.2021.3112174

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...