Implementation of Unusual Human Activity Detection in Warehouse Using SSD-Reference-Cited by-同舟云学术

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Implementation of Unusual Human Activity Detection in Warehouse Using SSD

Published:2022 Issue: Volume: Page:847-857
ISSN:2195-3988
Container-title:Proceedings of the International Conference on Cognitive and Intelligent Computing
language:
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Author:

Visuwasam L. Maria Michael,Kalpana G.,Dhinakaran K.,Kumar N. Kallish,Manigandan V.

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-19-2350-0_80

Reference15 articles.

1. Amrutha C, Jyotsna C, Amudha J (2020) Deep learning approach for suspicious activity detection from surveillance video. In: 2020 2nd international conference on innovative mechanisms for industry applications (ICIMIA). https://doi.org/10.1109/icimia48430.2020.9074920

2. Singh V, Singh S, Gupta P (2020) Real-time anomaly recognition through CCTV using neural networks. Procedia Comput Sci 173:254–263. https://doi.org/10.1016/j.procs.2020.06.030

3. Basha A, Parthasarathy P, Vivekanandan S (2019) Detection of suspicious human activity based on CNN-DBNN algorithm for video surveillance applications. In: 2019 innovations in power and advanced computing technologies (i-PACT). https://doi.org/10.1109/i-pact44901.2019.8960085

4. Kong X, Gao H, Alfarraj O, Ni Q, Zheng C, Shen G (2020) HUAD: hierarchical urban anomaly detection based on spatio-temporal data. IEEE Access 8:26573–26582. https://doi.org/10.1109/access.2020.2971341

5. Kapoor A, Biswas KK, Hanmandlu M (2017) Unusual human activity detection using Markov logic networks. In: 2017 IEEE international conference on identity, security and behavior analysis (ISBA). https://doi.org/10.1109/isba.2017.7947700

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1. Pattern Recognition Algorithm to Detect Suspicious Activities;2023 International Conference on Sustainable Computing and Smart Systems (ICSCSS);2023-06-14

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