Convolutional neural networks or vision transformers: Who will win the race for action recognitions in visual data?
Understanding actions in videos remains a significant challenge in computer vision, which
has been the subject of several pieces of research in the last decades. Convolutional neural …
has been the subject of several pieces of research in the last decades. Convolutional neural …
V2x-seq: A large-scale sequential dataset for vehicle-infrastructure cooperative perception and forecasting
Utilizing infrastructure and vehicle-side information to track and forecast the behaviors of
surrounding traffic participants can significantly improve decision-making and safety in …
surrounding traffic participants can significantly improve decision-making and safety in …
High-definition map representation techniques for automated vehicles
Many studies in the field of robot navigation have focused on environment representation
and localization. The goal of map representation is to summarize spatial information in …
and localization. The goal of map representation is to summarize spatial information in …
Driver stress detection via multimodal fusion using attention-based CNN-LSTM
Stress has been identified as one of major contributing factors in car crashes due to its
negative impact on driving performance. It is in urgent need that the stress levels of drivers …
negative impact on driving performance. It is in urgent need that the stress levels of drivers …
Flow-based feature fusion for vehicle-infrastructure cooperative 3d object detection
Cooperatively utilizing both ego-vehicle and infrastructure sensor data can significantly
enhance autonomous driving perception abilities. However, the uncertain temporal …
enhance autonomous driving perception abilities. However, the uncertain temporal …
Transiff: An instance-level feature fusion framework for vehicle-infrastructure cooperative 3d detection with transformers
Cooperation between vehicles and infrastructure is vital to enhancing the safety of
autonomous driving. Two significant and contradictory challenges now stand in the …
autonomous driving. Two significant and contradictory challenges now stand in the …
Automatic driver stress level classification using multimodal deep learning
Stress has been identified as one of the contributing factors to vehicle crashes which create
a significant cost in terms of loss of life and productivity for governments and societies …
a significant cost in terms of loss of life and productivity for governments and societies …
End-to-end federated learning for autonomous driving vehicles
In recent years, with the development of computation capability in devices, companies are
eager to investigate and utilize suitable ML/DL methods to improve their service quality …
eager to investigate and utilize suitable ML/DL methods to improve their service quality …
Social coordination and altruism in autonomous driving
Despite the advances in the autonomous driving domain, autonomous vehicles (AVs) are
still inefficient and limited in terms of cooperating with each other or coordinating with …
still inefficient and limited in terms of cooperating with each other or coordinating with …
A multi-neural network acceleration architecture
A cost-effective multi-tenant neural network execution is becoming one of the most important
design goals for modern neural network accelerators. For example, as emerging AI services …
design goals for modern neural network accelerators. For example, as emerging AI services …