Results 201 to 210 of about 26,569 (314)

Graph Neural Networks for Vehicular Social Networks: Trends, Challenges, and Opportunities

Graph Neural Networks (GNNs) have emerged as a powerful tool for modeling complex, interconnected data, making them particularly well-suited for enabling various applications in Intelligent Transportation Systems (ITS).
Hamrouni, Aymen, Binshaflout, Elham, Ghazzai, Hakim   +2 more
core   +1 more source

Continual Learning for Multimodal Data Fusion of a Soft Gripper

Advanced Robotics Research, EarlyView.
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley   +1 more source

Federated Learning over MU-MIMO Vehicular Networks. [PDF]

Entropy (Basel)
Raftopoulou M, da Silva JMB, Litjens R, Poor HV, Van Mieghem P.   +4 more
europepmc   +1 more source

CM-CPPA: Chaotic Map-Based Conditional Privacy-Preserving Authentication Scheme in 5G-Enabled Vehicular Networks. [PDF]

Sensors (Basel), 2022
Al-Shareeda MA, Manickam S, Mohammed BA, Al-Mekhlafi ZG, Qtaish A, Alzahrani AJ, Alshammari G, Sallam AA, Almekhlafi K.   +8 more
europepmc   +1 more source

A Soft Robotic Fish With a Dielectric Elastomer Actuator Body and Negative Stiffness Spine

Advanced Robotics Research, EarlyView.
This work introduces a bio‐mimetic soft robotic fish driven by fiber‐reinforced dielectric elastomer actuators integrated as its body. By prestretching this active skin against a flexible spine, a negative stiffness system is created, enabling large‐amplitude bending.
Markus Koenigsdorff, Simon Holzer, Stefania Konstantinidi, Yoan Civet, Yves Perriard   +4 more
wiley   +1 more source

Efficient traffic management with adaptive SDN in vehicular networks. [PDF]

Sci Rep
Rajan SJ, Narayanaswamy S, Balashanmugam T, Sengottaiyan K, Selvaraj A, Majumder P, Al-Rasheed A, Getahun M, Soufiene BO.   +8 more
europepmc   +1 more source

Robotic Control for Human–Robot Collaborative Assembly Based on Digital Human Model and Reinforcement Learning

Advanced Robotics Research, EarlyView.
This work presents a robotic control method for human–robot collaborative assembly based on a biomechanics‐constrained digital human model. Reinforcement learning is used to generate physiologically plausible human motion trajectories, which are integrated into a virtual environment for robot control learning.
Bitao Yao, Hongzhou Ai, Wenjun Xu, Zude Zhou, Lihui Wang   +4 more
wiley   +1 more source

BHFVAL: Block chain-Enabled Hierarchical Federated Variational Auto encoder Framework for Secure Intrusion Detection in Vehicular Networks. [PDF]

Sci Rep
Visuvanathan GE, Sayeed MS, Yogarayan S.
europepmc   +1 more source

Towards the Design of Efficient and Secure Architecture for Software-Defined Vehicular Networks. [PDF]

Sensors (Basel), 2021
Adnan M, Iqbal J, Waheed A, Amin NU, Zareei M, Umer A, Mohamed EM.   +6 more
europepmc   +1 more source

Multimodal Human–Robot Interaction Using Human Pose Estimation and Local Large Language Models

Advanced Robotics Research, EarlyView.
A multimodal human–robot interaction framework integrates human pose estimation (HPE) and a large language model (LLM) for gesture‐ and voice‐based robot control. Speech‐to‐text (STT) enables voice command interpretation, while a safety‐aware arbitration mechanism prioritizes gesture input for rapid intervention.
Nasiru Aboki, Ilche Georgievski, Marco Aiello   +2 more
wiley   +1 more source