Aerial LaneNet: Lane-marking semantic segmentation in aerial imagery using wavelet-enhanced cost-sensitive symmetric fully convolutional neural networks
The knowledge about the placement and appearance of lane markings is a prerequisite for
the creation of maps with high precision, necessary for autonomous driving, infrastructure …
the creation of maps with high precision, necessary for autonomous driving, infrastructure …
Fusionlane: Multi-sensor fusion for lane marking semantic segmentation using deep neural networks
Effective semantic segmentation of lane marking is crucial for construction of high-precision
lane level maps. In recent years, a number of different methods for semantic segmentation of …
lane level maps. In recent years, a number of different methods for semantic segmentation of …
Multi-class lane semantic segmentation using efficient convolutional networks
Lane detection plays an important role in a self-driving vehicle. Several studies leverage a
semantic segmentation network to extract robust lane features, but few of them can …
semantic segmentation network to extract robust lane features, but few of them can …
Scale sensitive neural network for road segmentation in high-resolution remote sensing images
X Tan, Z Xiao, Q Wan, W Shao - IEEE Geoscience and Remote …, 2020 - ieeexplore.ieee.org
Road segmentation in remote sensing images has been widely used in many fields.
Semantic segmentation, based on deep learning, has become a hot topic for road …
Semantic segmentation, based on deep learning, has become a hot topic for road …
VLDNet: Vision-based lane region detection network for intelligent vehicle system using semantic segmentation
Detection of lane region under the road boundary is an imperative module for intelligent
vehicle system. Lane markings provide separate regions on the road for the vehicles to …
vehicle system. Lane markings provide separate regions on the road for the vehicles to …
Robust u-net-based road lane markings detection for autonomous driving
The rapid development of artificial intelligence leads to many studies on autonomous robot
and self-driving vehicles, in which, autonomous driving plays one of the most important roles …
and self-driving vehicles, in which, autonomous driving plays one of the most important roles …
El-gan: Embedding loss driven generative adversarial networks for lane detection
M Ghafoorian, C Nugteren, N Baka… - proceedings of the …, 2018 - openaccess.thecvf.com
Convolutional neural networks have been successfully applied to semantic segmentation
problems. However, there are many problems that are inherently not pixel-wise classification …
problems. However, there are many problems that are inherently not pixel-wise classification …
Multitask attention network for lane detection and fitting
Many CNN-based segmentation methods have been applied in lane marking detection
recently and gain excellent success for a strong ability in modeling semantic information …
recently and gain excellent success for a strong ability in modeling semantic information …
[HTML][HTML] Road segmentation of remotely-sensed images using deep convolutional neural networks with landscape metrics and conditional random fields
Object segmentation of remotely-sensed aerial (or very-high resolution, VHS) images and
satellite (or high-resolution, HR) images, has been applied to many application domains …
satellite (or high-resolution, HR) images, has been applied to many application domains …
LDNet: End-to-end lane marking detection approach using a dynamic vision sensor
Modern vehicles are equipped with various driver-assistance systems, including automatic
lane keeping, which prevents unintended lane departures. Traditional lane detection …
lane keeping, which prevents unintended lane departures. Traditional lane detection …