Real-time transportation surveillance is an essential part of the intell...
The conventional Minimum Error Entropy criterion (MEE) has its limitatio...
Quantifying the performance bound of an integrated localization and
comm...
The recent release of very large language models such as PaLM and GPT-4 ...
Skin diseases are among the most prevalent health issues, and accurate
c...
Liver tumor segmentation and classification are important tasks in compu...
Asymmetry is a crucial characteristic of bilateral mammograms (Bi-MG) wh...
Magnetic resonance imaging (MRI) is the most sensitive technique for bre...
Multi-sequence MRI is valuable in clinical settings for reliable diagnos...
We study variance reduction methods for extragradient (EG) algorithms fo...
Accurate control of a humanoid robot's global position (i.e., its
three-...
The presence of non-homogeneous haze can cause scene blurring, color
dis...
Bagging is a useful method for large-scale statistical analysis, especia...
The rapid emergence of massive datasets in various fields poses a seriou...
Modern statistical analysis often encounters high dimensional models but...
The recently released ChatGPT has demonstrated surprising abilities in
n...
We introduce a new algorithm and software for solving linear equations i...
We consider the problem of large-scale Fisher market equilibrium computa...
Financial Distress Prediction plays a crucial role in the economy by
acc...
Magnetic resonance imaging (MRI) is highly sensitive for lesion detectio...
Multi-sequence MRIs can be necessary for reliable diagnosis in clinical
...
In this paper, we introduce a novel variation of model-agnostic
meta-lea...
The task of referring video object segmentation aims to segment the obje...
In this paper, we introduce second order and fourth order space
discreti...
Controller design for bipedal walking on dynamic rigid surfaces (DRSes),...
Recent research about camouflaged object detection (COD) aims to segment...
Statistical inference under market equilibrium effects has attracted
inc...
It is well known that it is difficult to have a reliable and robust fram...
We study a practical yet hasn't been explored problem: how a drone can
p...
RS-like locally repairable codes (LRCs) based on polynomial evaluation w...
In unsupervised domain adaptive (UDA) semantic segmentation, the distill...
Robotic ultrasound (US) imaging aims at overcoming some of the limitatio...
For massive large-scale tasks, a multi-robot system (MRS) can effectivel...
Real-world text applications often involve composing a wide range of tex...
Locally repairable codes(LRCs) play important roles in distributed stora...
As a rising task, panoptic segmentation is faced with challenges in both...
Ultrasound (US) is one of the most common medical imaging modalities sin...
Video question answering (VideoQA) is challenging given its multimodal
c...
Rumor detection has become an emerging and active research field in rece...
We propose modeling raw functional data as a mixture of a smooth functio...
We establish a general optimization framework for the design of automate...
We consider the problem of fairly allocating items to a set of individua...
Modern deep neural networks (DNNs) are vulnerable to adversarial attacks...
State estimation for legged locomotion over a dynamic rigid surface (DRS...
The world is currently experiencing an ongoing pandemic of an infectious...
In this paper, we introduce a Matlab program method to compute Carleman
...
Performing single image holistic understanding and 3D reconstruction is ...
Momentum methods have been shown to accelerate the convergence of the
st...
Distributed multi-party learning provides an effective approach for trai...
The occupancy grid map is a critical component of autonomous positioning...