• Composition Loss for Counting, Density Map Estimation and Localization in Dense Crowds 

      Idrees H.; Tayyab M.; Athrey K.; Zhang D.; Al-Maadeed, Somaya; ... more authors ( Springer Verlag , 2018 , Conference Paper)
      With multiple crowd gatherings of millions of people every year in events ranging from pilgrimages to protests, concerts to marathons, and festivals to funerals; visual crowd analysis is emerging as a new frontier in ...
    • iCAFE: Intelligent Congestion Avoidance and Fast Emergency services 

      Siddiqua A.; Shah M.A.; Khattak H.A.; Ud Din I.; Guizani M. ( Elsevier B.V. , 2019 , Article)
      Content Centric Network (CCN)has been envisioned as a paradigm shift from client server architecture. In smart cities, transportation plays an important role where integrated services facilitate citizens through the ease ...
    • VisDrone-CC2020: The Vision Meets Drone Crowd Counting Challenge Results 

      Du D.; Wen L.; Zhu P.; Fan H.; Hu Q.; ... more authors ( Springer Science and Business Media Deutschland GmbH , 2020 , Conference Paper)
      Crowd counting on the drone platform is an interesting topic in computer vision, which brings new challenges such as small object inference, background clutter and wide viewpoint. However, there are few algorithms focusing ...