In this paper, a power-constrained hybrid automatic repeat request (HARQ...
Open-set image recognition is a challenging topic in computer vision. Mo...
Compliance with traffic laws is a fundamental requirement for human driv...
Sparse-view computed tomography (CT) has been adopted as an important
te...
Interaction between the background vehicles (BVs) and automated vehicles...
Various human activities can be abstracted into a sequence of actions in...
Federated learning enables multiple hospitals to cooperatively learn a s...
Token filtering to reduce irrelevant tokens prior to self-attention is a...
Trajectory prediction is one of the key components of the autonomous dri...
Large language models like ChatGPT have recently demonstrated impressive...
Click-based interactive segmentation (IS) aims to extract the target obj...
This paper introduces XFL, an industrial-grade federated learning projec...
Peridynamic (PD) theory is significant and promising in engineering and
...
Although a typical autopilot system far surpasses humans in term of sens...
Source-free domain adaptation, where only a pre-trained source model is ...
Motion prediction is essential for safe and efficient autonomous driving...
An accurate trajectory prediction is crucial for safe and efficient
auto...
During X-ray computed tomography (CT) scanning, metallic implants carryi...
Triggered by the success of transformers in various visual tasks, the sp...
Autonomous driving confronts great challenges in complex traffic scenari...
Perception algorithms in autonomous driving systems confront great chall...
Integrating free-text explanations to in-context learning of large langu...
Automated machine learning has been widely explored to reduce human effo...
Building dialogue systems requires a large corpus of annotated dialogues...
This paper investigates the performance of Multiple-input multiple-outpu...
Reconfigurable intelligent surface (RIS) has recently attracted a spurt ...
The outage performance of multiple-input multiple-output (MIMO) techniqu...
This paper focuses on boosting the performance of small cell networks (S...
The combination between non-orthogonal multiple access (NOMA) and hybrid...
To support massive connectivity and boost spectral efficiency for intern...
Although current deep learning-based methods have gained promising
perfo...
3D Multi-object tracking (MOT) ensures consistency during continuous dyn...
Intersection is one of the most challenging scenarios for autonomous dri...
Recent work has shown that large pretrained Language Models (LMs) can no...
Semantic image editing utilizes local semantic label maps to generate th...
Inspired by the great success of deep neural networks, learning-based me...
Self-driving vehicles have their own intelligence to drive on open roads...
In this paper we investigate the variable coefficient two-sided fraction...
Motivated by their recent advances, deep learning techniques have been w...
During the computed tomography (CT) imaging process, metallic implants w...
Semiparametric joint models of longitudinal and competing risks data are...
As a common weather, rain streaks adversely degrade the image quality. H...
Existing work on automated hate speech classification assumes that the
d...
Kidney transplantation can significantly enhance living standards for pe...
Code search is an important and frequent activity for developers using
c...
Decision-making strategy for autonomous vehicles de-scribes a sequence o...
Single image deraining is an important yet challenging issue due to the
...
Digital quadruplets aiming to improve road safety, traffic efficiency, a...
This work optimizes the highway decision making strategy of autonomous
v...
Energy management strategies (EMSs) are the most significant components ...