Revolutionizing Video Event Detection: An Efficient Approach Utilizing Temporal Convolutional Neural Networks Using Real-time Performance-Reference-Cited by-同舟云学术

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Revolutionizing Video Event Detection: An Efficient Approach Utilizing Temporal Convolutional Neural Networks Using Real-time Performance

Published:2023-12-04 Issue: Volume:2 Page:1-6
ISSN:
Container-title:2023 3rd International Conference on Mobile Networks and Wireless Communications (ICMNWC)
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Author:

Alzubaidi Laith H.¹,Kumar Bura Vijay²,Alassedi Zainab³,Hussein A. H. A.⁴,N Rajesh⁵

Affiliation:

1. The Islamic University,Najaf,Iraq

2. School of Computer Science and Artificial Intelligence, SR University,Warangal,Telangana,India

3. National University of Science and Technology,Dhi Qar,Iraq

4. College of Pharmacy, Ahl Al Bayt University,Karbala,Iraq

5. Nitte Meenakshi Institute of Technology,Department of Electronics and Communication Engineering,Bengaluru,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10435701/10435648/10435845.pdf?arnumber=10435845

Reference16 articles.

1. A Deep Learning-Based Approach for Inappropriate Content Detection and Classification of YouTube Videos

2. An Efficient Dimension Reduction based Fusion of CNN and SVM Model for Detection of Abnormal Incident in Video Surveillance

3. EADN: An Efficient Deep Learning Model for Anomaly Detection in Videos

4. Logistic Sine Map (LSM) Based Partial Image Encryption

5. Deep learning and handcrafted features for one-class anomaly detection in UAV video

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