Sensors (Basel, Switzerland)
Apr 12, 2022
Recognizing various abnormal human activities from video is very challenging. This problem is also greatly influenced by the lack of datasets containing various abnormal human activities. The available datasets contain various human activities, but o...
IEEE transactions on neural networks and learning systems
Apr 4, 2022
Spiking neural networks (SNNs) are considered as a potential candidate to overcome current challenges, such as the high-power consumption encountered by artificial neural networks (ANNs); however, there is still a gap between them with respect to the...
IEEE transactions on neural networks and learning systems
Apr 4, 2022
Deep learning models achieve impressive performance for skeleton-based human action recognition. Graph convolutional networks (GCNs) are particularly suitable for this task due to the graph-structured nature of skeleton data. However, the robustness ...
Computational intelligence and neuroscience
Apr 4, 2022
Human Activity Recognition is an active research area with several Convolutional Neural Network (CNN) based features extraction and classification methods employed for surveillance and other applications. However, accurate identification of HAR from ...
Sensors (Basel, Switzerland)
Mar 29, 2022
Over the past decade, gait recognition had gained a lot of attention in various research and industrial domains. These include remote surveillance, border control, medical rehabilitation, emotion detection from posture, fall detection, and sports tra...
Computational intelligence and neuroscience
Mar 26, 2022
With the extensive application of virtual technology and simulation algorithm, motion behavior recognition is widely used in various fields. The original neural network algorithm cannot solve the problem of data redundancy in behavior recognition, an...
Computational intelligence and neuroscience
Mar 18, 2022
One of a very significant computer vision task in many real-world applications is traffic sign recognition. With the development of deep neural networks, state-of-art performance traffic sign recognition has been provided in recent five years. Gettin...
PloS one
Mar 17, 2022
Most deep learning-based action recognition models focus only on short-term motions, so the model often causes misjudgments of actions that are combined by multiple processes, such as long jump, high jump, etc. The proposal of Temporal Segment Networ...
Scientific reports
Mar 14, 2022
Gesture recognition is one of the most popular techniques in the field of computer vision today. In recent years, many algorithms for gesture recognition have been proposed, but most of them do not have a good balance between recognition efficiency a...
Scientific reports
Mar 8, 2022
There has been significant progress in skeleton-based action recognition. Human skeleton can be naturally structured into graph, so graph convolution networks have become the most popular method in this task. Most of these state-of-the-art methods op...