High‐accuracy vehicle lamp detection for real‐time night‐time traffic surveillance

2020 ◽  
Vol 14 (13) ◽  
pp. 1923-1934
Author(s):  
Wen‐Kai Tsai ◽  
Hung‐Ju Chen
Keyword(s):  
Real Time ◽  
High Accuracy ◽  
Traffic Surveillance ◽  
Night Time

Real Time Person Recognition and Attendance Marking Using Holistic Based Approach

2017 ◽  
Vol 7 (7) ◽  
pp. 302
Author(s):  
Reshma P ◽  
Muneer VK ◽  
Muhammed Ilyas P
Keyword(s):  
Face Recognition ◽  
Real Time ◽  
High Accuracy ◽  
Efficient Technique ◽  
Human Face ◽  
Traditional Methods ◽  
Person Recognition ◽  
The Face

Face recognition is a challenging task for the researches. It is very useful for personal verification and recognition and also it is very difficult to implement due to all different situation that a human face can be found. This system makes use of the face recognition approach for the computerized attendance marking of students or employees in the room environment without lectures intervention or the employee. This system is very efficient and requires very less maintenance compared to the traditional methods. Among existing methods PCA is the most efficient technique. In this project Holistic based approach is adapted. The system is implemented using MATLAB and provides high accuracy.

scholarly journals Augmented Reality Maintenance Assistant Using YOLOv5

2021 ◽  
Vol 11 (11) ◽  
pp. 4758
Author(s):  
Ana Malta ◽  
Mateus Mendes ◽  
Torres Farinha
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Object Recognition ◽  
Augmented Reality ◽  
Real Time ◽  
Recognition System ◽  
High Accuracy ◽  
Video Streams ◽  
The Neural Network ◽  
Deep Learning Neural Network

Maintenance professionals and other technical staff regularly need to learn to identify new parts in car engines and other equipment. The present work proposes a model of a task assistant based on a deep learning neural network. A YOLOv5 network is used for recognizing some of the constituent parts of an automobile. A dataset of car engine images was created and eight car parts were marked in the images. Then, the neural network was trained to detect each part. The results show that YOLOv5s is able to successfully detect the parts in real time video streams, with high accuracy, thus being useful as an aid to train professionals learning to deal with new equipment using augmented reality. The architecture of an object recognition system using augmented reality glasses is also designed.

scholarly journals Real-Time Detection of Daytime and Night-Time Fire Hotspots from Geostationary Satellites

2021 ◽  
Vol 13 (9) ◽  
pp. 1627
Author(s):  
Chermelle B. Engel ◽  
Simon D. Jones ◽  
Karin J. Reinke
Keyword(s):  
Real Time ◽  
Infrared Imaging ◽  
Night Time ◽  
Clear Link ◽  
Radiative Power ◽  
Biogeographical Region ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Fire Radiative Power

This paper introduces an enhanced version of the Biogeographical Region and Individual Geostationary HHMMSS Threshold (BRIGHT) algorithm. The algorithm runs in real-time and operates over 24 h to include both daytime and night-time detections. The algorithm was executed and tested on 12 months of Himawari-8 data from 1 April 2019 to 31 March 2020, for every valid 10-min observation. The resulting hotspots were compared to those from the Visible Infrared Imaging Radiometer Suite (VIIRS) and the Moderate Resolution Imaging Spectroradiometer (MODIS). The modified BRIGHT hotspots matched with fire detections in VIIRS 96% and MODIS 95% of the time. The number of VIIRS and MODIS hotspots with matches in the coincident modified BRIGHT dataset was lower (at 33% and 46%, respectively). This paper demonstrates a clear link between the number of VIIRS and MODIS hotspots with matches and the minimum fire radiative power considered.

scholarly journals Caffeine may disrupt the impact of real-time drowsiness on cognitive performance: a double-blind, placebo-controlled small-sample study

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
E. Aidman ◽  
M. Balin ◽  
K. Johnson ◽  
S. Jackson ◽  
G. M. Paech ◽  
...  
Keyword(s):  
Real Time ◽  
Cognitive Performance ◽  
Small Sample ◽  
Night Time ◽  
Double Blind ◽  
Infra Red ◽  
Procedural Decisions ◽  
Performance Gains ◽  
The Impact ◽  
Modest Reduction

AbstractCaffeine is widely used to promote alertness and cognitive performance under challenging conditions, such as sleep loss. Non-digestive modes of delivery typically reduce variability of its effect. In a placebo-controlled, 50-h total sleep deprivation (TSD) protocol we administered four 200 mg doses of caffeine-infused chewing-gum during night-time circadian trough and monitored participants' drowsiness during task performance with infra-red oculography. In addition to the expected reduction of sleepiness, caffeine was found to disrupt its degrading impact on performance errors in tasks ranging from standard cognitive tests to simulated driving. Real-time drowsiness data showed that caffeine produced only a modest reduction in sleepiness (compared to our placebo group) but substantial performance gains in vigilance and procedural decisions, that were largely independent of the actual alertness dynamics achieved. The magnitude of this disrupting effect was greater for more complex cognitive tasks.

scholarly journals High-Accuracy Tracking Using Ultrawideband Signals for Enhanced Safety of Cyclists

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Davide Dardari ◽  
Nicoló Decarli ◽  
Anna Guerra ◽  
Ashraf Al-Rimawi ◽  
Víctor Marín Puchades ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Real Time ◽  
High Accuracy ◽  
Experimental Results ◽  
Localization Error ◽  
Localization System ◽  
Dynamic Conditions ◽  
The Road ◽  
Road Users

In this paper, an ultrawideband localization system to improve the cyclists’ safety is presented. The architectural solutions proposed consist of tags placed on bikes, whose positions have to be estimated, and anchors, acting as reference nodes, located at intersections and/or on vehicles. The peculiarities of the localization system in terms of accuracy and cost enable its adoption with enhanced risk assessment units situated on the infrastructure/vehicle, depending on the architecture chosen, as well as real-time warning to the road users. Experimental results reveal that the localization error, in both static and dynamic conditions, is below 50 cm in most of the cases.

Vision Based Real-time High-accuracy Automatic Counting with Applications for Smart Pharmacy

2021 ◽  
Author(s):  
Haotian Wu ◽  
YuRan Wang ◽  
Hongbin Ma ◽  
Baokui Li ◽  
Ying Jin
Keyword(s):  
Real Time ◽  
High Accuracy ◽  
Automatic Counting
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