Area of research
Computer Vision and Pattern Recognition · Artificial Intelligence
Research interest
Research interests include Human Pose and Action Recognition, Anomaly Detection Techniques and Applications, Video Surveillance and Tracking Methods, and Context-Aware Activity Recognition Systems.
Complex interaction recognition <i>via</i> advanced multilevel feature fusion and deep learning model
Automatic liver tumor segmentation of CT and MRI volumes using ensemble ResUNet-InceptionV4 model
Physical Exergames Movements and Pattern Recognition using Convolutional Neural Network
Towards Sustainable IoT: A Digital Signature‐Enhanced Federated Learning Approach
A Robust Model of Human Activity Recognition using Independent Component Analysis and XGBoost
A review of video-based human activity recognition: theory, methods and applications
Human Action Recognition Based on Embedded HMM
A Novel Full-Body and Geometric Features for Physical Sports Interaction Recognition
Enhanced Human Interaction Recognition Framework using Pyramid Matching and Deep Neural Network
Robust Deep Interaction Recognition Framework with Multi-Stage Feature Analysis
Efficient Breast Cancer Diagnosis from Complex Mammographic Images Using Deep Convolutional Neural Network
A Novel Framework for Human Action Recognition Based on Features Fusion and Decision Tree
A Novel Human Interaction Framework Using Quadratic Discriminant Analysis with HMM
A Deep Learning Approach for Liver and Tumor Segmentation in CT Images Using ResUNet