Deep video anomaly detection: Opportunities and challenges

J Ren, F Xia, Y Liu, I Lee - 2021 international conference on …, 2021 - ieeexplore.ieee.org
Anomaly detection is a popular and vital task in various research contexts, which has been
studied for several decades. To ensure the safety of people's lives and assets, video …

Sentiment analysis of public social media as a tool for health-related topics

F Arias, MZ Nunez, A Guerra-Adames… - IEEE …, 2022 - ieeexplore.ieee.org
For decades, researchers have experimented with the possibility that machines can equal
human linguistic capabilities. Recently, advances in the field of natural language processing …

Uncertainty management in electricity demand forecasting with machine learning and ensemble learning: case studies of COVID-19 in the US metropolitans

MR Baker, KH Jihad, H Al-Bayaty, A Ghareeb… - … Applications of Artificial …, 2023 - Elsevier
Improving load forecasting is becoming increasingly crucial for power system management
and operational research. Disruptive influences can seriously impact both the supply and …

Unmasking cybercrime with artificial-intelligence-driven cybersecurity analytics

A Djenna, E Barka, A Benchikh, K Khadir - Sensors, 2023 - mdpi.com
Cybercriminals are becoming increasingly intelligent and aggressive, making them more
adept at covering their tracks, and the global epidemic of cybercrime necessitates significant …

[PDF][PDF] Violent Video Event Detection Based on Integrated LBP and GLCM Texture Features.

BH Lohithashva, VN Aradhya… - Revue d'Intelligence …, 2020 - researchgate.net
Accepted: 10 January 2020 Violent event detection is an interesting research problem and it
is a branch of action recognition and computer vision. The detection of violent events is …

[PDF][PDF] A survey on deep learning for financial risk prediction

K Peng, G Yan - Quantitative Finance and Economics, 2021 - aimspress.com
The rapid development of financial technology not only provides a lot of convenience to
people's production and life, but also brings a lot of risks to financial security. To prevent …

KNN-based machine learning classifier used on deep learned spatial motion features for human action recognition

K Paramasivam, MMR Sindha, SB Balakrishnan - Entropy, 2023 - mdpi.com
Human action recognition is an essential process in surveillance video analysis, which is
used to understand the behavior of people to ensure safety. Most of the existing methods for …

Tuna swarm algorithm with deep learning enabled violence detection in smart video surveillance systems

G Aldehim, MM Asiri, M Aljebreen, A Mohamed… - IEEE …, 2023 - ieeexplore.ieee.org
In smart video surveillance systems, violence detection becomes challenging to ensure
public safety and security. With the proliferation of surveillance cameras in public areas …

Understanding machine learning concepts

JM Aguiar-Pérez, MA Pérez-Juárez… - Encyclopedia of Data …, 2023 - igi-global.com
Artificial intelligence can be seen as the intelligence exhibited by machines. For an artificial
intelligence system to be able to take decisions based on the data available, different type of …

SVM directed machine learning classifier for human action recognition network

D Lamani, P Kumar, A Bhagyalakshmi, JM Shanthi… - Scientific Reports, 2025 - nature.com
Understanding human behavior and human action recognition are both essential
components of effective surveillance video analysis for the purpose of guaranteeing public …