Social Distancing and Face Mask Detection using Deep Learning Models: A Survey

Shetty, Sushmitha; Anand, Keerthi; Pooja, S; Punnya, K A; Priyanka, M

doi:10.1109/asiancon51346.2021.9544890

Cited by 9 publications

(3 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…for a query is the average of the precision values at all the recall levels where a relevant item was retrieved, see Eqs. [1,2,3,4] where 𝑘 is the number of queries, and 𝐴𝑃 𝑖 Is the average precision (𝐴𝑃) for a given query (𝑖), T.P. is True Positive, T.N.…”

Section: Experiments Results and Discussionmentioning

confidence: 99%

See 1 more Smart Citation

An automated AI and video measurement techniques for monitoring social distancing, mask detection, and facial temperature screening for COVID-19

Elhanashi

Saponara²,

Zheng

2023

Real-Time Processing of Image, Depth and Video Information 2023

View full text Add to dashboard Cite

COVID-19 is an infectious virus caused by acute respiratory syndrome SARS-CoV-2. It was first discovered in December 2019 in Wuhan, China. This ongoing pandemic caused infected cases, including many deaths around the world. Coronavirus is spread mainly by air droplets near the infected person due to sneezing, coughing, and talking. Pretrained DL models utilize large CNN layers, which require more disk size on IoTembedded devices and affect real-time detection. This research presents an integrated lightweight DL approach for real-time and multi-task (social distancing, mask detection, and facial temperature) video measurement to control the spread of coronavirus among individuals. The three tasks have used the most recent YOLO detectors (YOLOv7-tiny). It is an object detection model optimized based on the original YOLOv7 to simply the neural network architecture. The trained models have been evaluated in terms of mean average precision, Recall, and Precision to assess the algorithm performance. The proposed approach has been deployed and executed on NVIDIA devices (Jetson nano, Jetson Xavier AGX) composed of visible and thermal cameras. The visible camera is used for face mask detection, while the thermal camera is used for facial temperature measurement and social distancing. This research enriched the prevention system of COVID-19 by the integrated approach compared to the state-of-the-art methodologies. In addition, we obtained promising results for real-time detection. The proposed approach is suitable for a surveillance system to monitor social distancing, Face mask detection, and measuring the facial temperature among individuals.

show abstract

Section: Experiments Results and Discussionmentioning

confidence: 99%

“…OVID-19 pandemic has brought about significant changes in how society functions, emphasizing maintaining social distancing and wearing masks to slow the spread of the virus [1][2][3]. To ensure that these protocols are being followed, there is a growing need for automated systems that can detect and measure compliance.…”

Section: Introductionmentioning

confidence: 99%

An automated AI and video measurement techniques for monitoring social distancing, mask detection, and facial temperature screening for COVID-19

Elhanashi

Saponara²,

Zheng

2023

Real-Time Processing of Image, Depth and Video Information 2023

View full text Add to dashboard Cite

show abstract

“…A disease detection and classification system based on Android was proposed by Tlhobogang and Wannous [11]. The arecanut diseases can be prevented by using machine learning models, various techniques have been employed such as deep learning [12], convolutional neural network (CNN) [13], [14], image processing [15], [16], K-means [17], [18], support vector machine (SVM) [19], learning and machine perception (LAMP) [20] and real time identification of diseases [21]. Also, a simple practical architecture with three stages illumination normalization, feces detection and trait identification for CNN classification is proposed [22].…”

Section: Introductionmentioning

confidence: 99%

Identification and categorization of diseases in arecanut: a machine learning approach

Hegde

Sadanand

Hegde

et al. 2023

IJEECS

View full text Add to dashboard Cite

Arecanut is one of the prominent commercial crops that are grown worldwide for traditional medicines, furniture, cosmetics, food, veterinary preparations, and textile industries. It experiences a variety of diseases during its existence, from the bottom to the tip. The conventional method for detection of diseases is through visual inspection and it is also necessary to have properly designed laboratories to check these harvests. It is a time consuming and tedious task to inspect these crops across wide acres of plantations. The proposed system has been developed that uses convolutional neural network (CNN) to identify and categorize diseases in arecanuts, trunks and leaves also suggesting effective preventative measures. Proprietary dataset consists of 1,100 photos of healthy and diseased arecas. The ratio between the train and test data is 80:20. Binary cross entropy is employed as the loss function for model construction, with accuracy serving as the metrics and Adam serving as the optimizing function. In identification and categorization of arecanut diseases, the suggested approach was shown to be efficient with 93.05% accuracy.

show abstract

Enhanced Anomaly Detection in Pandemic Surveillance Videos: An Attention Approach With EfficientNet-B0 and CBAM Integration

Ul Amin,

Sibtain Abbas,

Kim

et al. 2024

IEEE Access

View full text Add to dashboard Cite

Social Distancing and Face Mask Detection using Deep Learning Models: A Survey

Cited by 9 publications

References 23 publications

An automated AI and video measurement techniques for monitoring social distancing, mask detection, and facial temperature screening for COVID-19

An automated AI and video measurement techniques for monitoring social distancing, mask detection, and facial temperature screening for COVID-19

Identification and categorization of diseases in arecanut: a machine learning approach

Enhanced Anomaly Detection in Pandemic Surveillance Videos: An Attention Approach With EfficientNet-B0 and CBAM Integration

Contact Info

Product

Resources

About