Now showing items 1-20 of 170

    • Joint Resource Allocation and Link Adaptation for Ultra-Reliable and Low-Latency Services 

      Hossen, Md Arman; Vu, X. Thang; Nguyen, Van Dinh; Chatzinotas, Symeon; Ottersten, Bjorn (2023)
      With the emergence of ultra-reliable and low latency communication (URLLC) services, link adaptation (LA) plays a pivotal role in improving the robustness and reliability of communication networks via appropriate modulation ...
    • Robust educational dialogue act classifiers with low-resource and imbalanced datasets 

      Lin, Jionghao; Tan, Wei; Nguyen, Ngoc Dang; Lang, David; Du, Lan; Buntine, Wray; Beare, Richard; Chen, Guanliang; Gašević, Dragan (2023-04-15)
      Dialogue acts (DAs) can represent conversational actions of tutors or students that take place during tutoring dialogues. Automating the identification of DAs in tutoring dialogues is significant to the design of dialogue-based ...
    • FEDGRAD: Mitigating backdoor attacks in federated learning through local ultimate gradients inspection 

      Nguyen, Thuy Dung; Nguyen, Duy Anh; Wong, Kok-Seng; Pham, H. Hieu; Nguyen, Thanh Hung; Nguyen, Phi Le (2023-04-29)
      Federated learning (FL) enables multiple clients to train a model without compromising sensitive data. However, the decentralized nature of FL makes it susceptible to adversarial attacks, particularly backdoor insertion ...
    • A survey on out-of-distribution evaluation of neural NLP models 

      Li, Xinzhe; Liu, Ming; Gao, Shang; Buntine, Wray (2023-06-27)
      Adversarial robustness, domain generalization, and dataset biases are three active lines of research contributing to out-of-distribution (OOD) evaluation on neural NLP models. However, a comprehensive, integrated discussion ...
    • Efficient human vision inspired action recognition using adaptive spatiotemporal sampling 

      Mac, C. Khoi Nguyen; Do, N. Minh; Vo, P. Minh (2022-07-14)
      Adaptive sampling that exploits the spatiotemporal redundancy in videos is critical for always-on action recognition on wearable devices with limited computing and battery resources. The commonly used fixed sampling strategy ...
    • Revisiting reverse distillation for anomaly detection 

      Tran, Dinh Tien; Nguyen, Tuan Anh; Nguyen, Hoang Tran; Ta, Duc Huy; Duong, T. M. Soan; Nguyen, D. Tr. Chanh; Truong, Q. H. Steven (2023)
      Anomaly detection is an important application in large-scale industrial manufacturing. Recent methods for this task have demonstrated excellent accuracy but come with a latency trade-off. Memory based approaches with ...
    • Denoising diffusion medical models 

      Tran, Minh Quan; Pham, Ngoc Huy (2023-04-19)
      In this study, we introduce a generative model that can synthesize a large number of radiographical image/label pairs, and thus is asymptotically favorable to downstream activities such as segmentation in bio-medical image ...
    • Fairness enhancement of UAV systems with hybrid active-passive RIS 

      Nguyen, Thanh Nhan; Nguyen, Van Dinh; Nguyen, Van Hieu; Wu, Qingqing; Tölli, Antti; Chatzinotas, Symeon; Juntti, Markku (2023-09-20)
      We consider unmanned aerial vehicle (UAV)-enabled wireless systems where downlink communications between a multi-antenna UAV and multiple users are assisted by a hybrid active-passive reconfigurable intelligent surface ...
    • Enhancing few-shot image classification with cosine transformer 

      Nguyen, Quang Huy; Nguyen, Q. Cuong; Le, D. Dung; Pham, H. Hieu (2023-07-21)
      This paper addresses the few-shot image classification problem, where the classification task is performed on unlabeled query samples given a small amount of labeled support samples only. One major challenge of the few-shot ...
    • A novel transparency strategy-based data augmentation approach for BI-RADS classification of mammograms 

      Tran, B. Sam; Nguyen, T. X. Huyen; Phan, Chi; Nguyen, Q. Ha; Pham, H. Hieu (2023-04-17)
      Image augmentation techniques have been widely investigated to improve the performance of deep learning (DL) algorithms on mammography classification tasks. Recent methods have proved the efficiency of image augmentation ...
    • Slice-level detection of intracranial hemorrhage on CT using deep descriptors of adjacent slices 

      Ngo, T. Dat; Nguyen, T. B. Thao; Nguyen, T. Hieu; Nguyen, B. Dung; Nguyen, Q. Ha; Pham, H. Hieu (2023-04-17)
      The rapid development in representation learning techniques such as deep neural networks and the availability of large-scale, well-annotated medical imaging datasets have led to a rapid increase in the use of supervised ...
    • Ensemble learning of myocardial displacements for myocardial infarction detection in echocardiography 

      Nguyen, Tuan; Nguyen, Phi; Tran, Dai; Pham, Hung; Nguyen, Quang; Le, Thanh; Van, Hanh; Do, Bach; Tran, Phuong; Le, Vinh; Nguyen, Thuy; Tran, Long; Pham, Hieu (2023-10-13)
      Background: Early detection and localization of myocardial infarction (MI) can reduce the severity of cardiac damage through timely treatment interventions. In recent years, deep learning techniques have shown promise for ...
    • Robotic cardiac compression device using artificial muscle filaments for the treatment of heart failure 

      Phan, Thien Phuoc; Davies, James; Hoang, Thien Trung; Thai, Mai Thanh; Nguyen, Cong Chi; Ji, Adrienne; Zhu, Kefan; Sharma, Bibhu; Nicotra, Emanuele; Hayward, Christopher; Phan, Hoang Phuong; Lovell, Nigel H.; Do, Nho Thanh (2023)
      Heart failure occurs when the heart cannot pump adequate blood to the body, which afflicts over 60 million people worldwide. Its treatment options include physiotherapy, medication, mechanical heart support, heart surgery, ...
    • Joint preloading and bitrate adaptation for short video streaming 

      Nguyen, Tien Phong; Truong, Thu Huong; Pham, Ngoc Nam; Truong, Cong Thang; Nguyen, Duc (2023)
      Short videos have become one of the most popular content mobile users consume nowadays. However, unlike traditional videos, users watch many short videos each time and frequently skip those not of their interest. Not taking ...
    • A probabilistic framework for pruning transformers via a finite admixture of keys 

      Nguyen, M. Tan; Nguyen, Tam; Bui, Long; Do, Hai; Nguyen, Duy Khuong; Le, Duy Dung; Tran, The Hung; Ho, Nhat; Osher, Stan J.; Baraniuk, Richard G. (2023-04-11)
      Pairwise dot product-based self-attention is key to the success of transformers which achieve state-of-the-art performance across a variety of applications in language and vision, but are costly to compute. It has been ...
    • LOGOVIT: Local-global vision transformer for object re-identification 

      Phan, Nguyen; Tran, Sam; Nguyen, Tran Hoang; Ta, Duc Huy; Duong, T. M. Soan; Nguyen, D. Tr. Chanh; Dao, Huu Hung; Bui, Trung; Truong, Q. H. Steven (2023-06)
      Object re-identification (ReID) is prone to errors under variations in scale, illumination, complex background, and object occlusion scenarios. To overcome these challenges, attention mechanisms are employed to concentrate ...
    • Fairness-aware dynamic VNF mapping and scheduling in SDN/NFV-enabled satellite edge networks 

      Abreha, Haftay Gebreslasie; Chougrani, Houcine; Maity, Ilora; Chatzinotas, Symeon; Politis, Christos; Nguyen, Van Dinh (2023-09)
      Satellite edge computing (SEC) has emerged as a promising technology to deliver network services to remote users. Coupled with software-defined networking (SDN) and network function virtualization (NFV), SEC can provide ...
    • Overlapping Stevens-Johnson syndrome and DRESS syndrome caused by phenobarbital: A Vietnamese case report 

      Nguyen, Van Khiem; Vu, Van Quang; Tran, Hoang Mai; Nguyen, Quoc Huy; Le, Quynh Chi; Dang, Thi Cam Bang; Chu, Chi Hieu; Nguyen, Van Dinh (2023-11-07)
      Drug Reaction with Eosinophilia and Systemic Symptoms (DRESS) Syndrome and Stevens-Johnson Syndrome (SJS) are severe cutaneous adverse reactions to drugs. Those reactions which are rare in children can be especially severe ...
    • Bayesian estimate of mean proper scores for diversity-enhanced active learning 

      Tan, Wei; Buntine, Wray; Du, Lan (2023-12-15)
      The effectiveness of active learning largely depends on the sampling efficiency of the acquisition function. Expected Loss Reduction (ELR) focuses on a Bayesian estimate of the reduction in classification error, and more ...
    • QoE-aware video streaming over HTTP and software defined networking 

      Pham, Hong Thinh; Nguyen, Thanh Dat; Pham, Nam Ngoc; Nguyen, Thanh Huu; Truong, Huong Thu (2019-08-19)
      Due to the increase in video streaming traffic over the Internet, more innovative methods are in demand for improving both Quality of Experience (QoE) of users and Quality of Service (QoS) of providers. In recent years, ...

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