Empowering things with intelligence: a survey of the progress, challenges, and opportunities in artificial intelligence of things

J Zhang, D Tao - IEEE Internet of Things Journal, 2020‏ - ieeexplore.ieee.org
In the Internet-of-Things (IoT) era, billions of sensors and devices collect and process data
from the environment, transmit them to cloud centers, and receive feedback via the Internet …

Pedestrian trajectory prediction in pedestrian-vehicle mixed environments: A systematic review

M Golchoubian, M Ghafurian… - IEEE Transactions …, 2023‏ - ieeexplore.ieee.org
Planning an autonomous vehicle's (AV) path in a space shared with pedestrians requires
reasoning about pedestrians' future trajectories. A practical pedestrian trajectory prediction …

Safe planning in dynamic environments using conformal prediction

L Lindemann, M Cleaveland, G Shim… - IEEE Robotics and …, 2023‏ - ieeexplore.ieee.org
We propose a framework for planning in unknown dynamic environments with probabilistic
safety guarantees using conformal prediction. Particularly, we design a model predictive …

Stepwise goal-driven networks for trajectory prediction

C Wang, Y Wang, M Xu… - IEEE Robotics and …, 2022‏ - ieeexplore.ieee.org
We propose to predict the future trajectories of observed agents (eg, pedestrians or vehicles)
by estimating and using their goals at multiple time scales. We argue that the goal of a …

S2Looking: A satellite side-looking dataset for building change detection

L Shen, Y Lu, H Chen, H Wei, D **e, J Yue, R Chen… - Remote Sensing, 2021‏ - mdpi.com
Building-change detection underpins many important applications, especially in the military
and crisis-management domains. Recent methods used for change detection have shifted …

Removing raindrops and rain streaks in one go

R Quan, X Yu, Y Liang, Y Yang - Proceedings of the IEEE …, 2021‏ - openaccess.thecvf.com
Existing rain-removal algorithms often tackle either rain streak removal or raindrop removal,
and thus may fail to handle real-world rainy scenes. Besides, the lack of real-world deraining …

Attention-based interrelation modeling for explainable automated driving

Z Zhang, R Tian, R Sherony… - IEEE Transactions on …, 2022‏ - ieeexplore.ieee.org
Automated driving desires better performance on tasks like motion planning and interacting
with pedestrians in mixed-traffic environments. Deep learning algorithms can achieve high …

Predicting pedestrian crossing intention with feature fusion and spatio-temporal attention

D Yang, H Zhang, E Yurtsever… - IEEE Transactions …, 2022‏ - ieeexplore.ieee.org
Predicting vulnerableroad user behavior is an essential prerequisite for deploying
Automated Driving Systems (ADS) in the real-world. Pedestrian crossing intention should be …

Holistic LSTM for pedestrian trajectory prediction

R Quan, L Zhu, Y Wu, Y Yang - IEEE transactions on image …, 2021‏ - ieeexplore.ieee.org
Accurate predictions of future pedestrian trajectory could prevent a considerable number of
traffic injuries and improve pedestrian safety. It involves multiple sources of information and …

PIT: Progressive interaction transformer for pedestrian crossing intention prediction

Y Zhou, G Tan, R Zhong, Y Li… - IEEE Transactions on …, 2023‏ - ieeexplore.ieee.org
For autonomous driving, one of the major challenges is to predict pedestrian crossing
intention in ego-view. Pedestrian intention depends not only on their intrinsic goals but also …