24 citations · 32 across the 10 of their papers we have counts for
13 papers
Mining Cross-Modal Perception Gaps in Autonomous Driving: When Camera and LiDAR Disagree
Hongsen Cao, Mona Jaber, Shanxin Yuan +1
Multi-modal fusion for 3D object detection assumes that cameras and LiDAR are broadly complementary. In practice, how much each modality is trusted at a given location is decided b…
Beyond Dead Reckoning: A Point of View on Camera--DAS--GNSS Continuity in Road Tunnels
Lyes Saad Saoud, Hesham A. Rakha, Mona Jaber +1
Road tunnels remove satellite visibility where connected and automated vehicles still require continuous, attributable, and integrity-bounded positioning. This Point of View argues…
Putting Registers to Work: Task Registers for Token Pruning in Vision Transformers
Hongsen Cao, Mona Jaber, Shanxin Yuan +1
Token-pruning policies are usually designed for a single recognition pipeline, but pretrained Vision Transformers are reused across tasks with different spatial demands. We ask whi…
Reducing AoI and Improving Throughput for NOMA-assisted SGF Systems: A Hierarchical Learning Approach
Yuqin Liu, Mona Jaber, Yan Liu +1
A non-orthogonal multiple access (NOMA) assisted semi-grant-free (SGF) framework is proposed to enable channel access for grant-free users (GFUs) by using residual resources from g…
Intelligent Travel Activity Monitoring: Generalized Distributed Acoustic Sensing Approaches
Ruikang Zhong, Chia-Yen Chiang, Mona Jaber +2
Obtaining data on active travel activities such as walking, jogging, and cycling is important for refining sustainable transportation systems (STS). Effectively monitoring these ac…
A Survey on AI-driven Energy Optimisation in Terrestrial Next Generation Radio Access Networks
Kishan Sthankiya, Nagham Saeed, Greg McSorley +2
This survey uncovers the tension between AI techniques designed for energy saving in mobile networks and the energy demands those same techniques create. We compare modeling approa…
AI-Ready Energy Modelling for Next Generation RAN
Kishan Sthankiya, Keith Briggs, Mona Jaber +1
Recent sustainability drives place energy-consumption metrics in centre-stage for the design of future radio access networks (RAN). At the same time, optimising the trade-off betwe…
A low complexity contextual stacked ensemble-learning approach for pedestrian intent prediction
Chia-Yen Chiang, Yasmin Fathy, Gregory Slabaugh +1
Walking as a form of active travel is essential in promoting sustainable transport. It is thus crucial to accurately predict pedestrian crossing intention and avoid collisions, esp…
Enabling Distributed Generative Artificial Intelligence in 6G: Mobile Edge Generation
Ruikang Zhong, Xidong Mu, Mona Jaber +1
Mobile edge generation (MEG) is an emerging technology that allows the network to meet the challenging traffic load expectations posed by the rise of generative artificial intellig…
AllTheDocks road safety dataset: A cyclist's perspective and experience
Chia-Yen Chiang, Ruikang Zhong, Jennifer Ding +3
Active travel is an essential component in intelligent transportation systems. Cycling, as a form of active travel, shares the road space with motorised traffic which often affects…
Mobile Edge Generation: A New Era to 6G
Ruikang Zhong, Xidong Mu, Yimeng Zhang +2
A conception of mobile edge generation (MEG) is proposed, where generative artificial intelligence (GAI) models are distributed at edge servers (ESs) and user equipment (UE), enabl…
A Distributed Acoustic Sensor System for Intelligent Transportation using Deep Learning
Chia-Yen Chiang, Mona Jaber, Peter Hayward
Intelligent transport systems (ITS) are pivotal in the development of sustainable and green urban living. ITS is data-driven and enabled by the profusion of sensors ranging from pn…
Context-Aware Wireless Connectivity and Processing Unit Optimization for IoT Networks
Metin Ozturk, Attai Ibrahim Abubakar, Rao Naveed Bin Rais +3
A novel approach is presented in this work for context-aware connectivity and processing optimization of Internet of things (IoT) networks. Different from the state-of-the-art appr…