Serious games in science education: a systematic literature
Teaching science through computer games, simulations, and artificial intelligence (AI) is an
increasingly active research field. To this end, we conducted a systematic literature review …
increasingly active research field. To this end, we conducted a systematic literature review …
Human activity recognition: Review, taxonomy and open challenges
Nowadays, Human Activity Recognition (HAR) is being widely used in a variety of domains,
and vision and sensor-based data enable cutting-edge technologies to detect, recognize …
and vision and sensor-based data enable cutting-edge technologies to detect, recognize …
A new approach to dominant motion pattern recognition at the macroscopic crowd level
F Matkovic, M Ivasic-Kos, S Ribaric - Engineering applications of artificial …, 2022 - Elsevier
Automatic analysis and the recognition and prediction of the behaviour of large-scale
crowds in video-surveillance data is a research field of paramount importance for the …
crowds in video-surveillance data is a research field of paramount importance for the …
Blockchain-based event detection and trust verification using natural language processing and machine learning
Z Shahbazi, YC Byun - IEEE Access, 2021 - ieeexplore.ieee.org
Information sharing is one of the huge topics in social media platform regarding the daily
news related to events or disasters happens in nature or its human-made. The automatic …
news related to events or disasters happens in nature or its human-made. The automatic …
[PDF][PDF] Attention-based LSTM network for action recognition in sports
Understanding human action from the visual data is an important computer vision
application for video surveillance, sports player performance analysis, and many IoT …
application for video surveillance, sports player performance analysis, and many IoT …
Learning dual-pooling graph neural networks for few-shot video classification
We address the problem of few-shot video classification that learns classifiers for novel
concepts from only a few examples. Most current methods ignore to explicitly consider the …
concepts from only a few examples. Most current methods ignore to explicitly consider the …
Local–global transformer neural network for temporal action segmentation
X Tian, Y Jin, X Tang - Multimedia Systems, 2023 - Springer
The temporal action segmentation task is a branch of video understanding that aims to
predict what is happening in the action segments (comprising a series of consecutive action …
predict what is happening in the action segments (comprising a series of consecutive action …
Real-time anomaly detection on surveillance video with two-stream spatio-temporal generative model
Abnormal detection of surveillance video is of great significance to social security and the
protection of specific scenes. However, the existing methods fail to achieve a balance …
protection of specific scenes. However, the existing methods fail to achieve a balance …
Deep crowd anomaly detection: state-of-the-art, challenges, and future research directions
Crowd anomaly detection is one of the most popular topics in computer vision in the context
of smart cities. A plethora of deep learning methods have been proposed that generally …
of smart cities. A plethora of deep learning methods have been proposed that generally …
Survey on video anomaly detection in dynamic scenes with moving cameras
The increasing popularity of compact and inexpensive cameras, eg dash cameras, body
cameras, and cameras equipped on robots, has sparked a growing interest in detecting …
cameras, and cameras equipped on robots, has sparked a growing interest in detecting …