Large language models for uavs: Current state and pathways to the future
S Javaid, H Fahim, B He… - IEEE Open Journal of …, 2024 - ieeexplore.ieee.org
Unmanned Aerial Vehicles (UAVs) have emerged as a transformative technology across
diverse sectors, offering adaptable solutions to complex challenges in both military and …
diverse sectors, offering adaptable solutions to complex challenges in both military and …
A comprehensive survey on artificial intelligence for unmanned aerial vehicles
Artificial Intelligence (AI) is an emerging technology that finds its application in various
industries. Integration of AI in Unmanned Aerial Vehicles (UAVs) can lead to tremendous …
industries. Integration of AI in Unmanned Aerial Vehicles (UAVs) can lead to tremendous …
Trajectory-Prediction Techniques for Unmanned Aerial Vehicles (UAVs): A Comprehensive Survey
Unmanned Aerial Vehicles (UAVs) have witnessed remarkable significance in diverse
sectors, ranging from environmental monitoring, infrastructure inspection, disaster response …
sectors, ranging from environmental monitoring, infrastructure inspection, disaster response …
Social self-attention generative adversarial networks for human trajectory prediction
Predicting accurate human future trajectories is of critical importance for self-driving vehicles
if they are to navigate complex scenarios. Trajectories of humans are not only dependent on …
if they are to navigate complex scenarios. Trajectories of humans are not only dependent on …
STIF: A Spatial–Temporal Integrated Framework for End-to-End Micro-UAV Trajectory Tracking and Prediction With 4-D MIMO Radar
The early trajectory prediction of micro unmanned aerial vehicles (micro-UAVs) with random
behavior intentions facilitates the elimination of potential safety hazards. However, due to …
behavior intentions facilitates the elimination of potential safety hazards. However, due to …
An agile autonomous car driving assistance using hybrid optimization-based kernel support vector convolutional network
S Jeyalakshmi, S Ravikumar, R Lakshmi… - Expert Systems with …, 2024 - Elsevier
In robotic control systems, autonomous car driving is considered a complicated task. The
conventional modular techniques necessitate precise localization, planning, and mapping …
conventional modular techniques necessitate precise localization, planning, and mapping …
Adaptive Depth Graph Neural Network-based Dynamic Task Allocation for UAV-UGVs Under Complex Environments
Z Ma, J Xiong, H Gong, X Wang - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
This paper investigates dynamic task allocation (DTA) for unmanned aerial vehicles (UAVs)
and unmanned ground vehicles (UGVs) in complex urban environments using an adaptive …
and unmanned ground vehicles (UGVs) in complex urban environments using an adaptive …
-Sigmoid Activation-Based Long Short-Term Memory for Time-Series Data Classification
With the enhanced usage of artificial-intelligence-driven applications, the researchers often
face challenges in improving the accuracy of data classification models, while trading off the …
face challenges in improving the accuracy of data classification models, while trading off the …
LSTM-based Trajectory and Phase-Shift Prediction for RSMA Networks Assisted by AIRS
This paper investigates rate-splitting multiple access (RSMA) networks with multiusers
assisted by aerial intelligent reflecting surfaces (AIRS). To improve the sum-rate of the …
assisted by aerial intelligent reflecting surfaces (AIRS). To improve the sum-rate of the …
Multi-modal Data based Semi-Supervised Learning for Vehicle Positioning
O Huan, Y Yang, T Luo, M Chen - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
In this paper, a multi-modal data based semi-supervised learning (SSL) framework that
jointly use channel state information (CSI) data and RGB images for vehicle positioning is …
jointly use channel state information (CSI) data and RGB images for vehicle positioning is …