Video Anomaly Detection with Spatio-Temporal Inspired Deep Neural Networks (DNN)-Reference-Cited by-同舟云学术

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Video Anomaly Detection with Spatio-Temporal Inspired Deep Neural Networks (DNN)

Published:2023-09-14 Issue: Volume:10 Page:1112-1118
ISSN:
Container-title:2023 6th International Conference on Contemporary Computing and Informatics (IC3I)
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Author:

Gupta Anil Kumar¹,Sharma Rupak²,Ojha Rudra Pratap³

Affiliation:

1. SRMIST Modinagar,Department of Computer Science and Engineering,Ghaziabad,U.P.

2. Department of Computer Science and Engineering,Ghaziabad,U.P.

3. G.L. Bajaj Institute of Technology and Management (GLBITM) (Affiliated to AKTU),Department of Computer Science and Engineering,Greater Noida,Uttar Pradesh,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10397581/10397594/10397914.pdf?arnumber=10397914

Reference82 articles.

1. Latent Space Autoregression for Novelty Detection

2. Fast Temporal Video Segmentation Based on Krawtchouk-Tchebichef Moments

3. A Novel Technique of Mixed Gas Identification Based on the Group Method of Data Handling (GMDH) on Time-Dependent MOX Gas Sensor Data

4. Video parsing for abnormality detection

5. Learning object motion patterns for anomaly detection and improved object detection

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