Surveillance systems integration for real time object identification using weighted bounding single neural network

• Main Authors: Alimuin, Ryann, Guiron, Aldrich, Dadios, Elmer P.
• Format: text
• Published: Animo Repository 2017
• Subjects: Detectors; Expert systems (Computer science); Security systems; Manufacturing; Mechanical Engineering
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/2705
• Institution: De La Salle University

In this paper, an implementation of a single neural network that classifies objects using bounding boxes and class probabilities is utilized. This features are combined with a real time surveillance system that can identify multiple targets at the same time. YOLO9000 is a contemporary tool in object...