Mask Detection Based On Efficient-YOLO

Yi, Li; Yan, Jiayuan; Hu, Bin

doi:10.23919/ccc52363.2021.9549903

Cited by 6 publications

(7 citation statements)

References 22 publications

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“…YOLO is also a more efficient model. The paper [24] shows that, on the selfmade verification set, the algorithm's mAP is 86.92 percent, and the preset process may be accomplished in the actual identification process by operating the robot. Two state-ofthe-art object detection models, YOLOv3 and faster R-CNN were used to achieve the accuracy in the paper [25].…”

Section: Literature Reviewmentioning

confidence: 99%

An Automated Face-mask Detection System using YOLOv5 for Preventing Spread of COVID-19

Jishan¹,

Alam²,

Mazumder³

et al. 2023

IJC

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Object detection systems based on deep learning have been immensely successful incomplex object detection tasks images and have shown potential in a wide range of real-life applicationsincluding the COVID-19 pandemic. One of the key challenges in containing and mitigating the infectionamong the population is to ensure and enforce the proper use of face masks. The objective of this paperis to detect the proper use of facial masks among the urban population in a megacity. In this study, wetrained and validated a new dataset to detect images such as ‘with mask’, ‘without mask’, and ‘masknot in position’ using YOLOv5. The dataset is comprised of 6550 images with the three classes. Thedataset attained a commendable performance accuracy of 95% on mAP. This study can be implementedfor automated scanning for monitoring the proper use of face masks in different settings of public spaces.

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Section: Literature Reviewmentioning

confidence: 99%

An Automated Face-mask Detection System using YOLOv5 for Preventing Spread of COVID-19

Jishan¹,

Alam²,

Mazumder³

et al. 2023

IJC

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“…At the Politeknik Negeri Batam, an apparatus known as a face mask detector has been installed to detect face masks in real-time using the YOLO V4 deep learning algorithm [23]. The method that was used to identify face masks in this work [24] reached a high level of accuracy. It was accurate in both categorization and detection to a 96% degree.…”

Section: Literature Reviewmentioning

confidence: 99%

YOLOv3 and YOLOv5-based automated facial mask detection and recognition systems to prevent COVID-19 outbreaks

Jishan,

Bedushe,

Rifat

et al. 2023

SITech

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Object detection system in light of deep learning have been monstrously effective in complex item identification task images and have shown likely in an extensive variety of genuine applications counting the Coronavirus pandemic. Ensuring and enforcing the proper use of face masks is one of the main obstacles in containing and reducing the spread of the infection among the population. This paper aims to find out how the urban population of a megacity uses facial masks correctly. Using YOLOv3 and YOLOv5, we trained and validated a brand-new dataset to identify images as "with mask", "without mask", and "mask not in position". In the YOLOv3 we carried out three pre-trained models which are: YOLOv3, YOLOv3-tiny, and SPP-YOLOv3. In addition, we utilized five pre-trained models in the YOLOv5: YOLOv5n, YOLOv5s, YOLOv5m, YOLOv5l, and YOLOv5x. The dataset is included 6550 pictures with three classes. On mAP, the dataset achieved a commendable 95% performance accuracy. This research can be used to monitor the proper use of face masks in various public spaces through automated scanning.

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“…Only a handful of mask detection methods have been developed for use by robots and their onboard cameras [15][16][17][18][19][20].…”

Section: Autonomous Mask Detection By Robotsmentioning

confidence: 99%

“…In [16], a mask detection system that used a deep learning method with an improved YOLOv3 algorithm was developed for the small humanoid robot NAO. In the proposed method, an improved Darknet-53 with an EfficientNet attention mechanism (to increase image resolution) was used as the backbone.…”

Section: Autonomous Mask Detection By Robotsmentioning

confidence: 99%

“…To enforce the mandatory wearing of face masks while reducing the time-consuming and costly task for humans to check people as they enter buildings, outdoor venues, etc., automated monitoring systems have been integrated into security cameras [13], tablets [14], and robots [15][16][17][18][19][20]. Recent detection systems have also used deep learning to classify whether people are wearing or not wearing masks (binary classification) in 2D images and videos [21][22][23][24][25][26][27][28][29][30].…”

Section: Introductionmentioning

confidence: 99%

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Robust Face Mask Detection by a Socially Assistive Robot Using Deep Learning

Zhang,

Effati,

Tan

et al. 2023

Computers

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Wearing masks in indoor and outdoor public places has been mandatory in a number of countries during the COVID-19 pandemic. Correctly wearing a face mask can reduce the transmission of the virus through respiratory droplets. In this paper, a novel two-step deep learning (DL) method based on our extended ResNet-50 is presented. It can detect and classify whether face masks are missing, are worn correctly or incorrectly, or the face is covered by other means (e.g., a hand or hair). Our DL method utilizes transfer learning with pretrained ResNet-50 weights to reduce training time and increase detection accuracy. Training and validation are achieved using the MaskedFace-Net, MAsked FAces (MAFA), and CelebA datasets. The trained model has been incorporated onto a socially assistive robot for robust and autonomous detection by a robot using lower-resolution images from the onboard camera. The results show a classification accuracy of 84.13% for the classification of no mask, correctly masked, and incorrectly masked faces in various real-world poses and occlusion scenarios using the robot.

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Mask Detection Based On Efficient-YOLO

Cited by 6 publications

References 22 publications

An Automated Face-mask Detection System using YOLOv5 for Preventing Spread of COVID-19

An Automated Face-mask Detection System using YOLOv5 for Preventing Spread of COVID-19

YOLOv3 and YOLOv5-based automated facial mask detection and recognition systems to prevent COVID-19 outbreaks

Robust Face Mask Detection by a Socially Assistive Robot Using Deep Learning

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