Related Experiment Video

Updated: Jun 16, 2026

Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

10.7K

Intelligent Complementary Multi-Modal Fusion for Anomaly Surveillance and Security System.

Jae-Hyeok Jeong1, Hwan-Hee Jung2, Yong-Hoon Choi2

  • 1Department of Electronic Information System Engineering, Sangmyung University, Cheonan 31066, Republic of Korea.

Sensors (Basel, Switzerland)
|November 25, 2023
PubMed
Summary

This study introduces an advanced deep learning (DL) system for security anomaly detection and classification. The multi-modal fusion approach achieved 85% accuracy, significantly improving upon single-model performance.

Keywords:
3D convolutional autoencoderGTA datasetanomaly classificationanomaly detectionmulti-modalslowfastsurveillance and security

More Related Videos

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

559
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

3.8K

Related Concept Videos

Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...