[HTML][HTML] Energy-efficient inference on the edge exploiting TinyML capabilities for UAVs
In recent years, the proliferation of unmanned aerial vehicles (UAVs) has increased
dramatically. UAVs can accomplish complex or dangerous tasks in a reliable and cost …
dramatically. UAVs can accomplish complex or dangerous tasks in a reliable and cost …
Low-power deep learning edge computing platform for resource constrained lightweight compact UAVs
Abstract Unmanned Aerial Vehicles (UAVs), which can operate autonomously in dynamic
and complex environments, are becoming increasingly common. Deep learning techniques …
and complex environments, are becoming increasingly common. Deep learning techniques …
E2edgeai: Energy-efficient edge computing for deployment of vision-based dnns on autonomous tiny drones
Artificial Intelligence (AI) and Deep Neural Networks (DNNs) have attracted attention as a
solution within autonomous systems fields as they enable applications such as visual …
solution within autonomous systems fields as they enable applications such as visual …
Mavbench: Micro aerial vehicle benchmarking
B Boroujerdian, H Genc, S Krishnan… - 2018 51st annual …, 2018 - ieeexplore.ieee.org
Unmanned Aerial Vehicles (UAVs) are getting closer to becoming ubiquitous in everyday
life. Among them, Micro Aerial Vehicles (MAVs) have seen an outburst of attention recently …
life. Among them, Micro Aerial Vehicles (MAVs) have seen an outburst of attention recently …
BERRY: Bit Error Robustness for Energy-Efficient Reinforcement Learning-Based Autonomous Systems
Z Wan, N Chandramoorthy… - 2023 60th ACM/IEEE …, 2023 - ieeexplore.ieee.org
Autonomous systems, such as Unmanned Aerial Vehicles (UAVs), are expected to run
complex reinforcement learning (RL) models to execute fully autonomous position …
complex reinforcement learning (RL) models to execute fully autonomous position …
Deep reinforcement learning driven UAV-assisted edge computing
Unmanned aerial vehicles (UAVs) are playing a critical role in provisioning instant
connectivity and computational needs of Internet of Things Devices (IoTDs), especially in …
connectivity and computational needs of Internet of Things Devices (IoTDs), especially in …
An optimization framework for efficient vision-based autonomous drone navigation
Fully autonomous drones are a new emerging field that has enabled many applications
such as gas source leakage localization, wild-fire detection, smart agriculture, and search …
such as gas source leakage localization, wild-fire detection, smart agriculture, and search …
AI-based UAV navigation framework with digital twin technology for mobile target visitation
Abstract Unmanned Air Vehicles (UAVs), ie drones, have become a key enabler technology
of many reconnaissance applications in different fields, such as military, maritime, and …
of many reconnaissance applications in different fields, such as military, maritime, and …
[HTML][HTML] Robustifying the deployment of tinyml models for autonomous mini-vehicles
Standard-sized autonomous vehicles have rapidly improved thanks to the breakthroughs of
deep learning. However, scaling autonomous driving to mini-vehicles poses several …
deep learning. However, scaling autonomous driving to mini-vehicles poses several …
Offloading deep learning powered vision tasks from UAV to 5G edge server with denoising
S Ozer, HE Ilhan, MA Ozkanoglu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Offloading computationally heavy tasks from an unmanned aerial vehicle (UAV) to a remote
server helps improve battery life and can help reduce resource requirements. Deep learning …
server helps improve battery life and can help reduce resource requirements. Deep learning …