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Anomaly Detection by Predicting Future Frames using Convolu..:
, In:
2023 2nd International Conference on Paradigm Shifts in Communications Embedded Systems, Machine Learning and Signal Processing (PCEMS)
,
Patrikar, Devashree R.
;
Parate, Mayur Rajaram
- p. 1-6 , 2023
Link:
https://doi.org/10.1109/PCEMS58491.2023.10136044
RT T1 <cTitle>2023 2nd International Conference on Paradigm Shifts in Communications Embedded Systems, Machine Learning and Signal Processing (PCEMS)</cTitle>: T1 <Title>Anomaly Detection by Predicting Future Frames using Convolutional LSTM in Video Surveillance</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10136044&Exemplar=1&LAN=DE A1 Patrikar, Devashree R. A1 Parate, Mayur Rajaram YR 2023 K1 Training K1 Event detection K1 Convolution K1 Training data K1 Machine learning K1 Predictive models K1 Video surveillance K1 Video Surveillance K1 Anomaly Detection K1 Convolutional Long-Short Term Memory K1 Computer Vision SP 1 OP 6 LK http://dx.doi.org/https://doi.org/10.1109/PCEMS58491.2023.10136044 DO https://doi.org/10.1109/PCEMS58491.2023.10136044 SF ELIB - SuUB Bremen
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