3 citations · 7 across the 15 of their papers we have counts for
16 papers
Toward a Unified Semantic Loss Model for Deep JSCC-based Transmission of EO Imagery
Ti Ti Nguyen, Thanh-Dung Le, Vu Nguyen Ha +6
Modern Earth Observation (EO) systems increasingly rely on high-resolution imagery to support critical applications such as environmental monitoring, disaster response, and land-us…
Demonstrator Testbed for Effective Precoding in MEO Multibeam Satellites
Jorge L. González-Rios, Liz Martínez Marrero, Juan Duncan +6
The use of communication satellites in medium Earth orbit (MEO) is foreseen to provide quasi-global broadband Internet connectivity in the coming networking ecosystems. Multi-user…
Artificial Intelligence implementation of onboard flexible payload and adaptive beamforming using commercial off-the-shelf devices
Luis Manuel Garcés-Socarrás, Amirhosein Nik, Flor Ortiz +13
Very High Throughput satellites typically provide multibeam coverage, however, a common problem is that there can be a mismatch between the capacity of each beam and the traffic de…
A Semantic-Loss Function Modeling Framework With Task-Oriented Machine Learning Perspectives
Ti Ti Nguyen, Thanh-Dung Le, Vu Nguyen Ha +9
The integration of machine learning (ML) has significantly enhanced the capabilities of Earth Observation (EO) systems by enabling the extraction of actionable insights from comple…
On-Air Deep Learning Integrated Semantic Inference Models for Enhanced Earth Observation Satellite Networks
Hong-fu Chou, Vu Nguyen Ha, Prabhu Thiruvasagam +7
Earth Observation (EO) systems are crucial for cartography, disaster surveillance, and resource administration. Nonetheless, they encounter considerable obstacles in the processing…
Cognitive Semantic Augmentation LEO Satellite Networks for Earth Observation
Hong-fu Chou, Vu Nguyen Ha, Prabhu Thiruvasagam +7
Earth observation (EO) systems are essential for mapping, catastrophe monitoring, and resource management, but they have trouble processing and sending large amounts of EO data eff…