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Human Abnormal Activity Prediction of Long Short-Term Memor..:

, In: 2024 Ninth International Conference on Science Technology Engineering and Mathematics (ICONSTEM),

Prathima, Ch. ; Suhel, Shaik Muhammed ; Rajeti, Roje Spandana... - p. 1-7 , 2024

Link: https://doi.org/10.1109/ICONSTEM60960.2024.10568890

RT 
T1 <cTitle>2024 Ninth International Conference on Science Technology Engineering and Mathematics (ICONSTEM)</cTitle>: T1 <Title>Human Abnormal Activity Prediction of Long Short-Term Memory using CNNs and RNNs in Deep Learning</Title>

UL https://suche.suub.uni-bremen.de/peid=ieee-10568890&Exemplar=1&LAN=DE
				
A1 Prathima, Ch.
A1 Suhel, Shaik Muhammed
A1 Rajeti, Roje Spandana
A1 Naik, Mude Sai Kumar
A1 Chaithanya, Singamsetty Krishna
A1 Reddy, Nallabathini Prabhakar
YR 2024
K1 Analytical models
K1 Adaptation models
K1 Accuracy
K1 Video sequences
K1 Predictive models
K1 Spatiotemporal phenomena
K1 Convolutional neural networks
K1 Abnormal activity prediction
K1 CNN LSTM hybrid model
K1 Video analysis
K1 Spatial and temporal features
K1 Surveillance
K1 Anomaly detection
K1 Convolutional Neural Networks
K1 Long Short-Term Memory
K1 Robustness
K1 Real-world scenarios
SP 1
OP 7
LK http://dx.doi.org/https://doi.org/10.1109/ICONSTEM60960.2024.10568890
DO https://doi.org/10.1109/ICONSTEM60960.2024.10568890
SF ELIB - SuUB Bremen

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