Anomaly analysis in images and videos: A comprehensive review

TM Tran, TN Vu, ND Vo, TV Nguyen… - ACM Computing …, 2022‏ - dl.acm.org
Anomaly analysis is an important component of any surveillance system. In recent years, it
has drawn the attention of the computer vision and machine learning communities. In this …

Towards automatic anomaly detection in fisheries using electronic monitoring and automatic identification system

D Acharya, M Farazi, V Rolland, L Petersson… - Fisheries …, 2024‏ - Elsevier
To ensure sustainable fisheries, many complex on-vessel activities are periodically
monitored to provide data to assist the assessment of stock status and ensure fishery …

[HTML][HTML] Crowd anomaly detection in video frames using fine-tuned AlexNet model

AA Khan, MA Nauman, M Shoaib, R Jahangir… - Electronics, 2022‏ - mdpi.com
This study proposed an AlexNet-based crowd anomaly detection model in the video (image
frames). The proposed model was comprised of four convolution layers (CLs) and three …

Anomalous event detection and localization in dense crowd scenes

A Alhothali, A Balabid, R Alharthi, B Alzahrani… - Multimedia Tools and …, 2023‏ - Springer
Recognizing and localizing anomalous events in crowd scenes is a challenging problem
that has attracted the attention of researchers in computer vision. Surveillance cameras …

Scene perception guided crowd anomaly detection

X Zhang, D Ma, H Yu, Y Huang, P Howell, B Stevens - Neurocomputing, 2020‏ - Elsevier
Crowd anomaly detection has been a research hotspot in the field of video surveillance in
recent years. In most existing methods, the accuracy of anomaly detection dominantly relies …

[HTML][HTML] Object detection algorithms to identify skeletal components in carbonate cores

HL Dawson, CM John - Marine and Petroleum Geology, 2024‏ - Elsevier
Identification of constituent grains in carbonate rocks requires specialist experience. A
carbonate sedimentologist must be able to distinguish between skeletal grains that change …

Crowd density level estimation and anomaly detection using multicolumn multistage bilinear convolution attention network (MCMS-BCNN-Attention)

E Ekanayake, Y Lei, C Li - Applied Sciences, 2022‏ - mdpi.com
The detection of crowd density levels and anomalies is a hot topic in video surveillance.
Especially in human-centric action and activity-based movements. In some respects, the …

Improving video anomaly detection performance by mining useful data from unseen video frames

R Wu, S Li, C Chen, A Hao - Neurocomputing, 2021‏ - Elsevier
Existing state-of-the-a rt (SOTA) video anomaly detection methods have mainly focused on
the network design for obtaining their performance improvements. Different to the main …

Anomaly detection using convolutional spatiotemporal autoencoder

H Dhole, M Sutaone, V Vyas - 2019 10th International …, 2019‏ - ieeexplore.ieee.org
In this paper an efficient technique for detecting anomalies in videos is proposed. Most of the
applications of Convolutional Neural Networks (CNNs) are based on object detection and …

Ambient intelligence and IoT based decision support system for intruder detection

K Lashmi, AS Pillai - 2019 IEEE International conference on …, 2019‏ - ieeexplore.ieee.org
Ambient intelligence is an evolving discipline which brings intelligence to our daily life
through various domains comprising elderly assistance, preventive maintenance, video …