Abnormal operation recognition based on a spatiotemporal residual network-Reference-Cited by-同舟云学术

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Abnormal operation recognition based on a spatiotemporal residual network

Published:2023-06-19 Issue: Volume: Page:
ISSN:1380-7501
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Liu Linqi,Wang Xiuhui^ORCID,Huang Xiaofang,Bao Qifu,Li Xuesheng,Wang Yaru

Funder

Key Research and Development Project of Zhejiang Province

Natural Science Foundation of Zhejiang Province

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Link

https://link.springer.com/content/pdf/10.1007/s11042-023-15875-z.pdf

Reference30 articles.

1. Andrienko N, Andrienko G, Patterson F, Stange H (2020) Visual analysis of place connectedness by public transport. IEEE Trans Intell Transp Syst 21(8):3196–3208

2. Bi X, Yang S, Tong P (2022) Moving object detection based on fusion of depth information and rgb features. Sensors (Basel, Switzerland) 22

3. Bolle RM, Connell JH, Pankanti S, Ratha NK, Senior AW (2005) The relation between the ROC curve and the CMC. In Fourth IEEE Workshop on Automatic Identification Advanced Technologies (AutoID’05), pp 15–20

4. Bondalapati A, Bhavanam S, Reddy E (2021) Moving object detection based on unified model. J Ambient Intell Human Comput 12

5. Delibaşoğlu İ (2023) Moving object detection method with motion regions tracking in background subtraction. Signal, Image and Video Processing, pp 1–9

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