Nuclear Magnetic Resonance (NMR) spectroscopy has served as a powerful
a...
Multi-agent embodied tasks have recently been studied in complex indoor
...
Magnetic resonance imaging (MRI) is a principal radiological modality th...
Magnetic Resonance Spectroscopy (MRS) is an important non-invasive techn...
Soft-thresholding has been widely used in neural networks. Its basic net...
In this paper, a novel robotic grasping system is established to
automat...
Implicit regularization is an important way to interpret neural networks...
Recent deep learning is superior in providing high-quality images and
ul...
In this work, we propose a Physics-Informed Deep Diffusion magnetic reso...
The ability to handle objects in cluttered environment has been long
ant...
In the Vision-and-Language Navigation task, the embodied agent follows
l...
Early action prediction aims to recognize human actions from only a part...
Deep learning has shown astonishing performance in accelerated magnetic
...
Referring expressions are commonly used when referring to a specific tar...
In visual semantic navigation, the robot navigates to a target object wi...
In this paper, we propose a novel Knowledge-based Embodied Question Answ...
Objective: Magnetic Resonance Spectroscopy (MRS) is a noninvasive tool t...
Multi-dimensional NMR spectroscopy is an invaluable biophysical tool in
...
Robots have limited adaptation ability compared to humans and animals in...
Deep reinforcement learning has made significant progress in robotic
man...
Embodiment is an important characteristic for all intelligent agents
(cr...
In this paper,we propose a novel task of Manipulation Question
Answering...
Exponential functions are powerful tools to model signals in various
sce...
Since the concept of deep learning (DL) was formally proposed in 2006, i...
Magnetic resonance imaging has been widely applied in clinical diagnosis...
The boom of non-uniform sampling and compressed sensing techniques
drama...
Nuclear magnetic resonance (NMR) spectroscopy serves as an indispensable...
Signals are generally modeled as a superposition of exponential function...
Compressed sensing has shown great potentials in accelerating magnetic
r...
Objective: Improve the reconstructed image with fast and multi-class
dic...
Compressed sensing has shown great potential in reducing data acquisitio...