Zenseact open dataset: A large-scale and diverse multimodal dataset for autonomous driving
Existing datasets for autonomous driving (AD) often lack diversity and long-range
capabilities, focusing instead on 360* perception and temporal reasoning. To address this …
capabilities, focusing instead on 360* perception and temporal reasoning. To address this …
Openlane-v2: A topology reasoning benchmark for unified 3d hd mapping
Accurately depicting the complex traffic scene is a vital component for autonomous vehicles
to execute correct judgments. However, existing benchmarks tend to oversimplify the scene …
to execute correct judgments. However, existing benchmarks tend to oversimplify the scene …
The mapillary traffic sign dataset for detection and classification on a global scale
Traffic signs are essential map features for smart cities and navigation. To develop accurate
and robust algorithms for traffic sign detection and classification, a large-scale and diverse …
and robust algorithms for traffic sign detection and classification, a large-scale and diverse …
A comprehensive survey and analysis of traffic sign recognition systems with hardware implementation
The continuous evolution of autonomous vehicles technologies has significantly elevated
the capabilities of intelligent transportation and road safety. Among these advancements …
the capabilities of intelligent transportation and road safety. Among these advancements …
Object detection-based system for traffic signs on drone-captured images
M Naranjo, D Fuentes, E Muelas, E Diez, L Ciruelo… - Drones, 2023 - mdpi.com
The construction industry is on the path to digital transformation. One of the main challenges
in this process is inspecting, assessing, and maintaining civil infrastructures and …
in this process is inspecting, assessing, and maintaining civil infrastructures and …
Deep learning-based real-time traffic sign recognition system for urban environments
C Kim, J Park, Y Park, W Jung, Y Lim - Infrastructures, 2023 - mdpi.com
A traffic sign recognition system is crucial for safely operating an autonomous driving car
and efficiently managing road facilities. Recent studies on traffic sign recognition tasks show …
and efficiently managing road facilities. Recent studies on traffic sign recognition tasks show …
On salience-sensitive sign classification in autonomous vehicle path planning: Experimental explorations with a novel dataset
Safe path planning in autonomous driving is a complex task due to the interplay of static
scene elements and uncertain surrounding agents. While all static scene elements are a …
scene elements and uncertain surrounding agents. While all static scene elements are a …
Pakistani traffic-sign recognition using transfer learning
Initially, the traffic-sign recognition was done using the conventional image processing
techniques which are sluggish and can cause fatal delays in real-world implementations …
techniques which are sluggish and can cause fatal delays in real-world implementations …
[HTML][HTML] Image Synthesis Pipeline for CNN-Based Sensing Systems
V Frolov, B Faizov, V Shakhuro, V Sanzharov… - Sensors, 2022 - mdpi.com
The rapid development of machine learning technologies in recent years has led to the
emergence of CNN-based sensors or ML-enabled smart sensor systems, which are …
emergence of CNN-based sensors or ML-enabled smart sensor systems, which are …
Towards real-time traffic sign recognition via YOLO on a mobile GPU
NS Artamonov, PY Yakimov - Journal of Physics: Conference …, 2018 - iopscience.iop.org
Classification of objects in the video stream with the help of deep learning has gained
immense popularity nowadays. Considering many systems solving the classification …
immense popularity nowadays. Considering many systems solving the classification …