Tuan Hoang

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We propose a new remote multimodal biometric authentication framework based on fragile watermarking for transferring multi-biometrics over networks to server for authentication. A facial image is used as a container to embed other numeric biometrics features. The proposed framework enhances security and reduces bandwidths. In order to reduce error rates(More)
BACKGROUND Teamwork and successful communication are essential parts of any medical specialty, especially in the trauma setting. U.S. Navy physicians developed a course for deploying fleet surgical teams to reinforce teamwork, communication, and baseline knowledge of trauma management. METHOD The course combines 22 hours of classroom didactics along with(More)
In this paper, we propose a multi-biometrics authentication system based on our proposed priority-based watermarking method. We investigate how watermarking techniques affect the container, which is facial image used in further authentication steps. We conduct experiments on facial and fingerprint features using both priority-based watermarking method and(More)
Surgical and simulation development have always been closely associated with military activity. The last ten years have continued that trend, allowing for training in real time, under reality-based conditions, learning technical and clinical skills with the dynamic of true human factors and team training in the actual environment. We present data from(More)
This paper proposes a general aggregate model for improving performance of multi-class Brain-Computer Interface (BCI) systems. In BCI systems, activation and delay are well known issues in conducting experiments. The delay of meaningful brain signal depends on subjects, tasks and experimental design. Therefore, within a trial it is not easy to identify(More)
Common Spatial Pattern (CSP) is a state-of-the-art method for feature extraction in Brain-Computer Interface (BCI) systems. However it is designed for 2-class BCI classification problems. Current extensions of this method to multiple classes based on subspace union and covariance matrix similarity do not provide a high performance. This paper presents a new(More)
Convolutional Neural Network (CNN) is a very powerful approach to extract discriminative local descriptors for e ective image search. Recent work adopts ne-tuned strategies to further improve the discriminative power of the descriptors. Taking a di erent approach, in this paper, we propose a novel framework to achieve competitive retrieval performance.(More)
OBJECTIVE The high-stress, fast-paced environment of combat casualty care relies on effective teamwork and communication which translates into quality patient care. A training course was developed for U.S. Navy Fleet Surgical Teams to address these aspects of patient care by emphasizing efficiency and appropriate patient care. An effective training course(More)