Zobrazeno 1 - 10
of 1 049
pro vyhledávání: '"Hong, Choong"'
Beyond the success of Contrastive Language-Image Pre-training (CLIP), recent trends mark a shift toward exploring the applicability of lightweight vision-language models for resource-constrained scenarios. These models often deliver suboptimal perfor
Externí odkaz:
http://arxiv.org/abs/2412.03871
Low Earth orbit (LEO) satellites are capable of gathering abundant Earth observation data (EOD) to enable different Internet of Things (IoT) applications. However, to accomplish an effective EOD processing mechanism, it is imperative to investigate:
Externí odkaz:
http://arxiv.org/abs/2410.13602
Autor:
Zou, Luyao, Vo, Quang Hieu, Kim, Kitae, Le, Huy Q., Thwal, Chu Myaet, Zhang, Chaoning, Hong, Choong Seon
In this paper, cyber-attack prevention for the prosumer-based electric vehicle (EV) charging stations (EVCSs) is investigated, which covers two aspects: 1) cyber-attack detection on prosumers' network traffic (NT) data, and 2) cyber-attack interventi
Externí odkaz:
http://arxiv.org/abs/2410.13260
In this paper, a novel generative adversarial imitation learning (GAIL)-powered policy learning approach is proposed for optimizing beamforming, spectrum allocation, and remote user equipment (RUE) association in NTNs. Traditional reinforcement learn
Externí odkaz:
http://arxiv.org/abs/2409.18718
Autor:
Nguyen, Loc X., Hassan, Sheikh Salman, Tun, Yan Kyaw, Kim, Kitae, Han, Zhu, Hong, Choong Seon
The sixth-generation (6G) non-terrestrial networks (NTNs) are crucial for real-time monitoring in critical applications like disaster relief. However, limited bandwidth, latency, rain attenuation, long propagation delays, and co-channel interference
Externí odkaz:
http://arxiv.org/abs/2409.14726
In this study, we explore the efficacy of advanced pre-trained architectures, such as Vision Transformers (ViT), ConvNeXt, and Swin Transformers in enhancing Federated Domain Generalization. These architectures capture global contextual features and
Externí odkaz:
http://arxiv.org/abs/2409.13527
The proliferation of data-intensive and low-latency applications has driven the development of multi-access edge computing (MEC) as a viable solution to meet the increasing demands for high-performance computing and storage capabilities at the networ
Externí odkaz:
http://arxiv.org/abs/2408.12860
Earth observation satellites generate large amounts of real-time data for monitoring and managing time-critical events such as disaster relief missions. This presents a major challenge for satellite-to-ground communications operating under limited ba
Externí odkaz:
http://arxiv.org/abs/2408.03959
Combining different data modalities enables deep neural networks to tackle complex tasks more effectively, making multimodal learning increasingly popular. To harness multimodal data closer to end users, it is essential to integrate multimodal learni
Externí odkaz:
http://arxiv.org/abs/2407.15426
Autor:
Nguyen, Tung-Anh, Le, Long Tan, Nguyen, Tuan Dung, Bao, Wei, Seneviratne, Suranga, Hong, Choong Seon, Tran, Nguyen H.
Publikováno v:
IEEE/ACM Transactions on Networking On page(s): 1-16 Print ISSN: 1063-6692 Online ISSN: 1558-2566 Digital Object Identifier: 10.1109/TNET.2024.3423780
With the proliferation of the Internet of Things (IoT) and the rising interconnectedness of devices, network security faces significant challenges, especially from anomalous activities. While traditional machine learning-based intrusion detection sys
Externí odkaz:
http://arxiv.org/abs/2407.07421