Fully automated roadside parking spot detection in real time with deep learning

The smart teaching mode overcomes the shortcomings of traditional teaching online and offline, but there are certain deficiencies in the real-time feature extraction of teachers and students. In view of this, this study uses the particle swarm image recognition and deep learning technology to process the intelligent classroom video teaching image and extracts the classroom task features in real time and sends them to the teacher. In order to overcome the shortcomings of the premature convergence of the standard particle swarm optimization algorithm, an improved strategy for multiple particle swarm optimization algorithms is proposed. In order to improve the premature problem in the search performance algorithm of PSO algorithm, this paper combines the algorithm with the useful attributes of other algorithms to improve the particle diversity in the algorithm, enhance the global search ability of the particle, and achieve effective feature extraction. The research indicates that the method proposed in this paper has certain practical effects and can provide theoretical reference for subsequent related research.

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Deep Learning Technique for Real-time Traffic Light Detection by Automated Vehicles

International Journal of Computer Sciences and Engineering ◽

10.26438/ijcse/v6i7.387392 ◽

2018 ◽

Vol 6 (7) ◽

pp. 387-392

Author(s):

Priyanka S.N. ◽

Shashidhara H.S.

Keyword(s):

Deep Learning ◽

Real Time ◽

Automated Vehicles ◽

Traffic Light ◽

Light Detection ◽

Real Time Traffic ◽

Learning Technique

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Real-time Worker Safety Management System Using Deep Learning-based Video Analysis Algorithm

Korean Institute of Smart Media ◽

10.30693/smj.2020.9.3.25 ◽

2020 ◽

Vol 9 (3) ◽

pp. 25-30

Author(s):

So Yeon Jeon ◽

Jong Hwa Park ◽

Sang Byung Youn ◽

Young Soo Kim ◽

Yong Sung Lee ◽

...

Keyword(s):

Deep Learning ◽

Real Time ◽

Video Analysis ◽

Management System ◽

Safety Management ◽

Worker Safety ◽

Safety Management System ◽

Analysis Algorithm

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Real Time Gender and Age Prediction using Deep Learning Techniques

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.e2906.049620 ◽

2020 ◽

Vol 9 (6) ◽

pp. 797-801

Keyword(s):

Deep Learning ◽

Face Recognition ◽

Real Time ◽

Vital Role ◽

Learning Techniques ◽

Gender And Age ◽

The Face ◽

And Gender ◽

Gender Detection ◽

Age Prediction

Face recognition plays a vital role in security purpose. In recent years, the researchers have focused on the pose illumination, face recognition, etc,. The traditional methods of face recognition focus on Open CV’s fisher faces which results in analyzing the face expressions and attributes. Deep learning method used in this proposed system is Convolutional Neural Network (CNN). Proposed work includes the following modules: [1] Face Detection [2] Gender Recognition [3] Age Prediction. Thus the results obtained from this work prove that real time age and gender detection using CNN provides better accuracy results compared to other existing approaches.

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