[HTML][HTML] A survey on deep learning-based monocular spacecraft pose estimation: Current state, limitations and prospects
Estimating the pose of an uncooperative spacecraft is an important computer vision problem
for enabling the deployment of automatic vision-based systems in orbit, with applications …
for enabling the deployment of automatic vision-based systems in orbit, with applications …
Edge AI: A taxonomy, systematic review and future directions
Abstract Edge Artificial Intelligence (AI) incorporates a network of interconnected systems
and devices that receive, cache, process, and analyse data in close communication with the …
and devices that receive, cache, process, and analyse data in close communication with the …
Artificial intelligence in the IoT era: A review of edge AI hardware and software
T Sipola, J Alatalo, T Kokkonen… - 2022 31st Conference …, 2022 - ieeexplore.ieee.org
The modern trend of moving artificial intelligence computation near to the origin of data
sources has increased the demand for new hardware and software suitable for such …
sources has increased the demand for new hardware and software suitable for such …
A deep learning framework performance evaluation to use YOLO in Nvidia Jetson platform
DJ Shin, JJ Kim - Applied Sciences, 2022 - mdpi.com
Deep learning-based object detection technology can efficiently infer results by utilizing
graphics processing units (GPU). However, when using general deep learning frameworks …
graphics processing units (GPU). However, when using general deep learning frameworks …
[HTML][HTML] Comparative analysis of multiple YOLO-based target detectors and trackers for ADAS in edge devices
P Azevedo, V Santos - Robotics and Autonomous Systems, 2024 - Elsevier
Accurate detection and tracking of vulnerable road users and traffic objects represent vital
tasks for autonomous driving and driving assistance systems. The recent developments in …
tasks for autonomous driving and driving assistance systems. The recent developments in …
Characterizing the performance of accelerated jetson edge devices for training deep learning models
Deep Neural Networks (DNNs) have had a significant impact on domains like autonomous
vehicles and smart cities through low-latency inferencing on edge computing devices close …
vehicles and smart cities through low-latency inferencing on edge computing devices close …
A review of embedded machine learning based on hardware, application, and sensing scheme
Machine learning is an expanding field with an ever-increasing role in everyday life, with its
utility in the industrial, agricultural, and medical sectors being undeniable. Recently, this …
utility in the industrial, agricultural, and medical sectors being undeniable. Recently, this …
[HTML][HTML] A Review of Recent Hardware and Software Advances in GPU-Accelerated Edge-Computing Single-Board Computers (SBCs) for Computer Vision
Computer Vision (CV) has become increasingly important for Single-Board Computers
(SBCs) due to their widespread deployment in addressing real-world problems. Specifically …
(SBCs) due to their widespread deployment in addressing real-world problems. Specifically …
On-board small-scale object detection for unmanned aerial vehicles (UAVs)
Object detection is a critical task that becomes difficult when dealing with onboard detection
using aerial images and computer vision technique. The main challenges with aerial images …
using aerial images and computer vision technique. The main challenges with aerial images …
Energy efficiency in edge TPU vs. embedded GPU for computer-aided medical imaging segmentation and classification
In this work, we evaluate the energy usage of fully embedded medical diagnosis aids based
on both segmentation and classification of medical images implemented on Edge TPU and …
on both segmentation and classification of medical images implemented on Edge TPU and …