An Adaptive Framework for Anomaly Detection in Time-Series Audio-Visual Data-Reference-Cited by-同舟云学术

An Adaptive Framework for Anomaly Detection in Time-Series Audio-Visual Data

Published:2022 Issue: Volume:10 Page:36188-36199
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Kumari Pratibha¹^ORCID,Saini Mukesh¹^ORCID

Affiliation:

1. Department of Computer Science and Engineering, IIT Ropar, Rupnagar, India

Funder

Department Of Science & Technology (DST), Government of India for the Technology Innovation Hub at the IIT Ropar in the framework of National Mission on Interdisciplinary Cyber-Physical Systems

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09748166.pdf?arnumber=9748166

Reference59 articles.

1. A Multimodal Anomaly Detector for Robot-Assisted Feeding Using an LSTM-Based Variational Autoencoder

2. An introduction to hidden Markov models

3. Video Anomaly Detection Via Predictive Autoencoder With Gradient-Based Attention

4. Spatio-Temporal AutoEncoder for Video Anomaly Detection

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