Compare neural networks YOLOv3 ،
YOLOv5s،MobileNet-SSD V2 to detect face masks in real
time
Document Type : Original Article
Abstract
Surveys, evaluations using multiple cases show their true potential and there are important technologies in various fields. One of the most popular applications of concepts is object recognition and tracking. Recent products show promising results in this regard.These systems can be compared and compared, which analyzes the images and determines whether the person has used the mask correctly, incorrectly or not at all. Mask detection is performed on real-time video and surveillance systems using three widely used machine image algorithms: Yolon3, Yolon5 and MobileNet-SSD V1. Recognized. Will be judged.The performance results of the three algorithms for detecting the presence of a face mask on a person in real time are determined in terms of FPS
. (2022). Compare neural networks YOLOv3 ،
YOLOv5s،MobileNet-SSD V2 to detect face masks in real
time. Computing and distributed systems, 5(1), 49-55.
MLA
. "Compare neural networks YOLOv3 ،
YOLOv5s،MobileNet-SSD V2 to detect face masks in real
time", Computing and distributed systems, 5, 1, 2022, 49-55.
HARVARD
. (2022). 'Compare neural networks YOLOv3 ،
YOLOv5s،MobileNet-SSD V2 to detect face masks in real
time', Computing and distributed systems, 5(1), pp. 49-55.
CHICAGO
, "Compare neural networks YOLOv3 ،
YOLOv5s،MobileNet-SSD V2 to detect face masks in real
time," Computing and distributed systems, 5 1 (2022): 49-55,
VANCOUVER
. Compare neural networks YOLOv3 ،
YOLOv5s،MobileNet-SSD V2 to detect face masks in real
time. Computing and distributed systems. 2022;5(1):49-55 (In Persian).