A review of high-definition map creation methods for autonomous driving
Autonomous driving has been among the most popular and challenging topics in the past
few years. Among all modules in autonomous driving, High-definition (HD) map has drawn …
few years. Among all modules in autonomous driving, High-definition (HD) map has drawn …
Graph-based deep learning techniques for remote sensing applications: Techniques, taxonomy, and applications—A comprehensive review
In the last decade, there has been a significant surge of interest in machine learning,
primarily driven by advancements in deep learning (DL). DL has emerged as a powerful …
primarily driven by advancements in deep learning (DL). DL has emerged as a powerful …
Early detection of red palm weevil infestations using deep learning classification of acoustic signals
Abstract The Red Palm Weevil (RPW), also known as the palm weevil, is considered among
the world's most damaging insect pests of palms. Current detection techniques include the …
the world's most damaging insect pests of palms. Current detection techniques include the …
A hybrid privacy-preserving deep learning approach for object classification in very high-resolution satellite images
Deep learning (DL) has shown outstanding performances in many fields, including remote
sensing (RS). DL is turning into an essential tool for the RS research community. Recently …
sensing (RS). DL is turning into an essential tool for the RS research community. Recently …
Segment Anything Model for Road Network Graph Extraction
We propose SAM-Road an adaptation of the Segment Anything Model (SAM) for extracting
large-scale vectorized road network graphs from satellite imagery. To predict graph …
large-scale vectorized road network graphs from satellite imagery. To predict graph …
Sensor fusion in autonomous vehicle with traffic surveillance camera system: detection, localization, and AI networking
Complete autonomous systems such as self-driving cars to ensure the high reliability and
safety of humans need the most efficient combination of four-dimensional (4D) detection …
safety of humans need the most efficient combination of four-dimensional (4D) detection …
TAU: A framework for video-based traffic analytics leveraging artificial intelligence and unmanned aerial systems
Smart traffic engineering and intelligent transportation services are in increasing demand
from governmental authorities to optimize traffic performance and thus reduce energy costs …
from governmental authorities to optimize traffic performance and thus reduce energy costs …
Automatic extraction of bare soil land from high-resolution remote sensing images based on semantic segmentation with deep learning
C He, Y Liu, D Wang, S Liu, L Yu, Y Ren - Remote Sensing, 2023 - mdpi.com
Accurate monitoring of bare soil land (BSL) is an urgent need for environmental governance
and optimal utilization of land resources. High-resolution imagery contains rich semantic …
and optimal utilization of land resources. High-resolution imagery contains rich semantic …
High-definition map generation technologies for autonomous driving
Z Bao, S Hossain, H Lang, X Lin - arXiv preprint arXiv:2206.05400, 2022 - arxiv.org
Autonomous driving has been among the most popular and challenging topics in the past
few years. On the road to achieving full autonomy, researchers have utilized various …
few years. On the road to achieving full autonomy, researchers have utilized various …
[HTML][HTML] Near real-time flood mapping with weakly supervised machine learning
Advances in deep learning and computer vision are making significant contributions to flood
mapping, particularly when integrated with remotely sensed data. Although existing …
mapping, particularly when integrated with remotely sensed data. Although existing …