Generalized video anomaly event detection: Systematic taxonomy and comparison of deep models
Video Anomaly Detection (VAD) serves as a pivotal technology in the intelligent surveillance
systems, enabling the temporal or spatial identification of anomalous events within videos …
systems, enabling the temporal or spatial identification of anomalous events within videos …
TransCNN: Hybrid CNN and transformer mechanism for surveillance anomaly detection
Surveillance video anomaly detection (SVAD) is a challenging task due to the variations in
object scale, discrimination and unexpected events, the impact of the background, and the …
object scale, discrimination and unexpected events, the impact of the background, and the …
[HTML][HTML] An outliers detection and elimination framework in classification task of data mining
An outlier is a datum that is far from other data points in which it occurs. It can have a
considerable impact on the output. Therefore, removing or resolving it before the analysis is …
considerable impact on the output. Therefore, removing or resolving it before the analysis is …
Improving the efficiency of multistep short-term electricity load forecasting via R-CNN with ML-LSTM
Multistep power consumption forecasting is smart grid electricity management's most
decisive problem. Moreover, it is vital to develop operational strategies for electricity …
decisive problem. Moreover, it is vital to develop operational strategies for electricity …
Vision transformer attention with multi-reservoir echo state network for anomaly recognition
Anomalous event recognition requires an instant response to reduce the loss of human life
and property; however, existing automated systems show limited performance due to …
and property; however, existing automated systems show limited performance due to …
Deep learning for abnormal human behavior detection in surveillance videos—A survey
Detecting abnormal human behaviors in surveillance videos is crucial for various domains,
including security and public safety. Many successful detection techniques based on deep …
including security and public safety. Many successful detection techniques based on deep …
Prime: privacy-preserving video anomaly detection via motion exemplar guidance
Video anomaly detection (VAD) involves identifying events or behaviours in video
sequences that deviate from expected patterns. Most VAD models to date focus on seeking …
sequences that deviate from expected patterns. Most VAD models to date focus on seeking …
Stochastic video normality network for abnormal event detection in surveillance videos
Abstract Video Anomaly Detection (VAD) aims to automatically identify unexpected spatial–
temporal patterns to detect abnormal events in surveillance videos. Existing unsupervised …
temporal patterns to detect abnormal events in surveillance videos. Existing unsupervised …
Sequential attention mechanism for weakly supervised video anomaly detection
Surveillance cameras are installed across various sectors of a smart city in order to capture
ongoing events for monitoring purposes. The analysis of these surveillance videos is an …
ongoing events for monitoring purposes. The analysis of these surveillance videos is an …
Neuro-heuristic analysis of surveillance video in a centralized IoT system
D Połap - ISA transactions, 2023 - Elsevier
Security systems are based on the monitoring of specific areas of the facility. The cameras
record the selected place for the whole day. Unfortunately, it is difficult to automatically …
record the selected place for the whole day. Unfortunately, it is difficult to automatically …