Intelligent Mask Detection Using Deep Learning Techniques. Issue 1 (May 2021)
- Record Type:
- Journal Article
- Title:
- Intelligent Mask Detection Using Deep Learning Techniques. Issue 1 (May 2021)
- Main Title:
- Intelligent Mask Detection Using Deep Learning Techniques
- Authors:
- Anantha Prabha, P
Karthikeyan, G
Kuttralanathan, K
Manoj Venkatesun, M - Abstract:
- Abstract: Owing to the corona pandemic, the government has insisted on wearing a safety mask and maintaining 6 feet distance to get rid of CoronaVirus. The detection of people with or without masks is a challenge due to the impact of Covid pandemic. There are some models / systems which really reduce the manpower to notify the people. The existing system runs on the model: Yolov3, V G G, for face detection and MobileNetv2 for face recognition, object detection, and semantic segmentation inorder to detect the people with and without masks. The proposed system holds an approach of detecting human's faces and classifying them into people with and without masks which has been done using image processing and deep learning and our project runs u.3nder a model called Faster RCNN. Moreover, Faster R-CNN is more accurate while other models are faster. Being effective is not important but being efficient is way more important.
- Is Part Of:
- Journal of physics. Volume 1916:Issue 1(2021)
- Journal:
- Journal of physics
- Issue:
- Volume 1916:Issue 1(2021)
- Issue Display:
- Volume 1916, Issue 1 (2021)
- Year:
- 2021
- Volume:
- 1916
- Issue:
- 1
- Issue Sort Value:
- 2021-1916-0001-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-05
- Subjects:
- coronavirus -- pandemic -- face mask detection and recognition
Physics -- Congresses
530.5 - Journal URLs:
- http://www.iop.org/EJ/journal/1742-6596 ↗
http://ioppublishing.org/ ↗ - DOI:
- 10.1088/1742-6596/1916/1/012072 ↗
- Languages:
- English
- ISSNs:
- 1742-6588
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5036.223000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 25270.xml