Machine learning with data assimilation and uncertainty quantification for dynamical systems: a review
Data assimilation (DA) and uncertainty quantification (UQ) are extensively used in analysing
and reducing error propagation in high-dimensional spatial-temporal dynamics. Typical …
and reducing error propagation in high-dimensional spatial-temporal dynamics. Typical …
Anomaly detection using edge computing in video surveillance system
DR Patrikar, MR Parate - International Journal of Multimedia Information …, 2022 - Springer
The current concept of smart cities influences urban planners and researchers to provide
modern, secured and sustainable infrastructure and gives a decent quality of life to its …
modern, secured and sustainable infrastructure and gives a decent quality of life to its …
Self-supervised attentive generative adversarial networks for video anomaly detection
Video anomaly detection (VAD) refers to the discrimination of unexpected events in videos.
The deep generative model (DGM)-based method learns the regular patterns on normal …
The deep generative model (DGM)-based method learns the regular patterns on normal …
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 …
Vadclip: Adapting vision-language models for weakly supervised video anomaly detection
The recent contrastive language-image pre-training (CLIP) model has shown great success
in a wide range of image-level tasks, revealing remarkable ability for learning powerful …
in a wide range of image-level tasks, revealing remarkable ability for learning powerful …
A new comprehensive benchmark for semi-supervised video anomaly detection and anticipation
Semi-supervised video anomaly detection (VAD) is a critical task in the intelligent
surveillance system. However, an essential type of anomaly in VAD named scene …
surveillance system. However, an essential type of anomaly in VAD named scene …
Computer vision applications in intelligent transportation systems: a survey
As technology continues to develop, computer vision (CV) applications are becoming
increasingly widespread in the intelligent transportation systems (ITS) context. These …
increasingly widespread in the intelligent transportation systems (ITS) context. These …
NM-GAN: Noise-modulated generative adversarial network for video anomaly detection
D Chen, L Yue, X Chang, M Xu, T Jia - Pattern Recognition, 2021 - Elsevier
As an important and challenging task for intelligent video surveillance systems, video
anomaly detection is generally referred to as automatic recognition of video frames that …
anomaly detection is generally referred to as automatic recognition of video frames that …
Scene-aware context reasoning for unsupervised abnormal event detection in videos
In this paper, we propose a scene-aware context reasoning method that exploits context
information from visual features for unsupervised abnormal event detection in videos, which …
information from visual features for unsupervised abnormal event detection in videos, which …
Attention-based anomaly detection in multi-view surveillance videos
Anomaly detection is one of the most challenging tasks in visual understanding because
anomalous events are diverse and complicated. In this paper, we propose a future frame …
anomalous events are diverse and complicated. In this paper, we propose a future frame …