Weapons Detection for Security and Video Surveillance Using CNN and YOLO-V5s | Zendy

Abdul Hanan Ashraf | Zendy; Muhammad Imran | Zendy; Abdulrahman M. Qahtani | Zendy; Abdulmajeed Alsufyani | Zendy; Omar Almutiry | Zendy; Awais Mahmood | Zendy; Muhammad Attique | Zendy; Mohamed Habib | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Weapons Detection for Security and Video Surveillance Using CNN and YOLO-V5s

Author(s) -

Abdul Hanan Ashraf,

Muhammad Imran,

Abdulrahman M. Qahtani,

Abdulmajeed Alsufyani,

Omar Almutiry,

Awais Mahmood,

Muhammad Attique,

Mohamed Habib

Publication year - 2021

Publication title -

computers, materials and continua/computers, materials and continua (print)

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.788

H-Index - 40

eISSN - 1546-2226

pISSN - 1546-2218

DOI - 10.32604/cmc.2022.018785

Subject(s) - false positive paradox , computer science , frame rate , convolutional neural network , artificial intelligence , visibility , false positive rate , pedestrian detection , frame (networking) , object detection , computer vision , motion blur , overhead (engineering) , false positives and false negatives , real time computing , pattern recognition (psychology) , image (mathematics) , engineering , pedestrian , telecommunications , physics , transport engineering , optics , operating system

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research