2022
DOI: 10.1049/ipr2.12666
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Video abnormal behaviour detection based on pseudo‐3D encoder and multi‐cascade memory mechanism

Abstract: Frame prediction methods based on Auto-Encoder (AE) composed of convolutional neural networks (CNN) are very popular in detecting abnormal behaviour. The methods predict normal behaviour accurately and abnormal behaviour incorrectly, which is considered a criterion for abnormality discrimination. However, the emergence of problems such as too strong AE representation leading to detection failure, the insufficient ability of the network to extract spatio-temporal information, a large number of model parameters … Show more

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Cited by 3 publications
(1 citation statement)
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“…In this paper, a new network framework combining pseudo-3D convolution and multi-cascading memory mechanism was proposed to effectively solve these problems. Its detection efficiency and superiority were verified on public datasets 11 . In order to improve the data scarcity in supervised visual tasks, self supervised label enhancement technology has emerged, which has shown significant effects in the field of object detection.…”
Section: Related Workmentioning
confidence: 96%
“…In this paper, a new network framework combining pseudo-3D convolution and multi-cascading memory mechanism was proposed to effectively solve these problems. Its detection efficiency and superiority were verified on public datasets 11 . In order to improve the data scarcity in supervised visual tasks, self supervised label enhancement technology has emerged, which has shown significant effects in the field of object detection.…”
Section: Related Workmentioning
confidence: 96%