Applications of deep learning in intelligent transportation systems
AK Haghighat, V Ravichandra-Mouli… - Journal of Big Data …, 2020 - Springer
Abstract In recent years, Intelligent Transportation Systems (ITS) have seen efficient and
faster development by implementing deep learning techniques in problem domains which …
faster development by implementing deep learning techniques in problem domains which …
Deep learning in object detection: A review
Object detection continues to play a significant part in computer vision theory, study and
practical application. Conventional object detection algorithms were primarily derived from …
practical application. Conventional object detection algorithms were primarily derived from …
Deep learning for safe autonomous driving: Current challenges and future directions
Advances in information and signal processing technologies have a significant impact on
autonomous driving (AD), improving driving safety while minimizing the efforts of human …
autonomous driving (AD), improving driving safety while minimizing the efforts of human …
Attention-based interrelation modeling for explainable automated driving
Automated driving desires better performance on tasks like motion planning and interacting
with pedestrians in mixed-traffic environments. Deep learning algorithms can achieve high …
with pedestrians in mixed-traffic environments. Deep learning algorithms can achieve high …
Toward intelligent industrial informatics: A review of current developments and future directions of artificial intelligence in industrial applications
Research, the universal pursuit of new knowledge, is embarking on a fresh journey into
artificial intelligence (AI). ature reports that AI arose nine places to the fourth-most popular …
artificial intelligence (AI). ature reports that AI arose nine places to the fourth-most popular …
Comprehensive survey of machine learning approaches in cognitive radio-based vehicular ad hoc networks
Nowadays, machine learning (ML), which is one of the most rapidly growing technical tools,
is extensively used to solve critical challenges in various domains. Vehicular ad hoc network …
is extensively used to solve critical challenges in various domains. Vehicular ad hoc network …
Obstacle Detection for Intelligent Transportation Systems Using Deep Stacked Autoencoder and -Nearest Neighbor Scheme
Obstacle detection is an essential element for the development of intelligent transportation
systems so that accidents can be avoided. In this paper, we propose a stereovision-based …
systems so that accidents can be avoided. In this paper, we propose a stereovision-based …
Unsupervised obstacle detection in driving environments using deep-learning-based stereovision
A vision-based obstacle detection system is a key enabler for the development of
autonomous robots and vehicles and intelligent transportation systems. This paper …
autonomous robots and vehicles and intelligent transportation systems. This paper …
Artificial intelligence-based surveillance system for railway crossing traffic
The application of Artificial Intelligence (AI) based techniques has strong potential to
improve safety and efficiency in data-driven Intelligent Transportation Systems (ITS) as well …
improve safety and efficiency in data-driven Intelligent Transportation Systems (ITS) as well …
[HTML][HTML] Intelligent transportation systems: A survey on modern hardware devices for the era of machine learning
The increasing complexity of Intelligent Transportation Systems (ITS), that comprise a wide
variety of applications and services, has imposed a necessity for high-performance Modern …
variety of applications and services, has imposed a necessity for high-performance Modern …