All Outputs (4)

A bidirectional Siamese recurrent neural network for accurate gait recognition using body landmarks (2024)
Journal Article
Progga, P. H., Rahman, M. J., Biswas, S., Ahmed, M. S., Anwary, A. R., & Shatabda, S. (2024). A bidirectional Siamese recurrent neural network for accurate gait recognition using body landmarks. Neurocomputing, 605, Article 128313. https://doi.org/10.1016/j.neucom.2024.128313

Gait recognition is a significant biometric technique for person identification, particularly in scenarios where other physiological biometrics are impractical or ineffective. In this paper, we address the challenges associated with gait recognition... Read More about A bidirectional Siamese recurrent neural network for accurate gait recognition using body landmarks.

An Enhanced Ensemble Deep Neural Network Approach for Elderly Fall Detection System Based on Wearable Sensors (2023)
Journal Article
Mohammad, Z., Anwary, A. R., Mridha, M. F., Shovon, M. S. H., & Vassallo, M. (2023). An Enhanced Ensemble Deep Neural Network Approach for Elderly Fall Detection System Based on Wearable Sensors. Sensors, 23(10), Article 4774. https://doi.org/10.3390/s23104774

Fatal injuries and hospitalizations caused by accidental falls are significant problems among the elderly. Detecting falls in real-time is challenging, as many falls occur in a short period. Developing an automated monitoring system that can predict... Read More about An Enhanced Ensemble Deep Neural Network Approach for Elderly Fall Detection System Based on Wearable Sensors.

YOLO-Fish: A robust fish detection model to detect fish in realistic underwater environment (2022)
Journal Article
Muksit, A. A., Hasan, F., Hasan Bhuiyan Emon, M. F., Haque, M. R., Anwary, A. R., & Shatabda, S. (2022). YOLO-Fish: A robust fish detection model to detect fish in realistic underwater environment. Ecological Informatics, 72, Article 101847. https://doi.org/10.1016/j.ecoinf.2022.101847

Over the last few years, several research works have been performed to monitor fish in the underwater environment aimed for marine research, understanding ocean geography, and primarily for sustainable fisheries. Automating fish identification is ver... Read More about YOLO-Fish: A robust fish detection model to detect fish in realistic underwater environment.

Gait quantification and visualization for digital healthcare (2020)
Journal Article
Anwary, A. R., Yu, H., & Vassallo, M. (2020). Gait quantification and visualization for digital healthcare. Health Policy and Technology, 9(2), 204-212. https://doi.org/10.1016/j.hlpt.2019.12.004

Gait abnormalities are common in clinical practice and there is a global imperative to improve technologies that facilitate their detection, evaluation, monitoring and management. Real time evaluation using digital technology supports the development... Read More about Gait quantification and visualization for digital healthcare.