Large-scale deployed cameras in the automated container terminal (ACT) area helps on-site
staff better identify unexpected yet emergency events by monitoring port personnel …

Autonomous vehicles promise to revolutionize society and improve the daily life of many,
making them a coveted aim for a vast research community. To enable complex reasoning in …

Multi-modal learning has made impressive progress in autonomous driving by leveraging
information from multiple sensors. Existing feature fusion methods make decisions by …

Object detection is an essential computer vision task that identifies and locates objects
within images or videos and is crucial for applications such as autonomous driving, robotics …

Abstract Background and Objective At present, the COVID-19 epidemic is still spreading
worldwide and wearing a mask in public areas is an effective way to prevent the spread of …

Automatic voice pathology detection using non-invasive techniques that utilize patients'
speech and electroglottograph (EGG) signals play a vital role in diagnosis and early medical …

In this paper, a large‐scale dataset called the Iran Autonomous Driving Dataset (IADD) is
presented, aiming to improve the generalization capability of the deep networks outside of …

Autonomous vehicles are equipped with complimentary sensors to perceive the
environment accurately. Deep learning models have proven to be the most effective …

In texture classification, local binary pattern (LBP) is currently one of the most widely-
concerned feature encoding models. Most existing LBP-based texture classification methods …

The recent nonrepetitive scanning (NRS)-light detection and ranging (LiDAR), using rosette
or Lissajous curves, has higher spatial scanning efficiency and lower price than traditional …