We present DFormer, a novel RGB-D pretraining framework to learn transfe...
Convolutional neural networks excel in histopathological image
classific...
This work introduces a novel control strategy called Iterative Linear
Qu...
This work aims to push the limits of agility for bipedal robots by enabl...
This paper presents a safety-critical locomotion control framework for
q...
We present a reinforcement learning (RL) framework that enables quadrupe...
Recent years have seen a surge in commercially-available and affordable
...
We address the problem of enabling quadrupedal robots to perform precise...
This paper tackles the problem of robots collaboratively towing a load w...
Ultrasound examination is widely used in the clinical diagnosis of thyro...
Bridging model-based safety and model-free reinforcement learning (RL) f...
In this paper, we propose a multi-domain control parameter learning fram...
Our goal is to enable robots to perform functional tasks in emotive ways...
Quadrupeds are strong candidates for navigating challenging environments...
Electrocardiogram (ECG) signals play critical roles in the clinical scre...
Safety is one of the fundamental problems in robotics. Recently, one-ste...
An autonomous robot that is able to physically guide humans through narr...
Developing robust walking controllers for bipedal robots is a challengin...
The normal distributions transform (NDT) is an effective paradigm for th...
Recently, Expectation-maximization (EM) algorithm has been introduced as...
Intra-cardiac Echocardiography (ICE) has been evolving as a real-time im...
Creating robots with emotional personalities will transform the usabilit...
Annotating histopathological images is a time-consuming andlabor-intensi...
Label distribution learning (LDL) is an interpretable and general learni...
Recently, the motion averaging method has been introduced as an effectiv...
This study investigates the problem of multi-view clustering, where mult...
Recently, label distribution learning (LDL) has drawn much attention in
...
Registration of multi-view point sets is a prerequisite for 3D model
rec...
Recently, deep neural networks have demonstrated comparable and even bet...
Zero-shot learning, which aims to recognize new categories that are not
...
Multi-view clustering is an important and fundamental problem. Many
mult...
Many multi-view clustering methods have been proposed with the popularit...
This paper proposes a global approach for the multi-view registration of...
Aggregating deep convolutional features into a global image vector has
a...
Mapping in the GPS-denied environment is an important and challenging ta...
For the registration of partially overlapping point clouds, this paper
p...
Multi-view registration is a fundamental but challenging problem in 3D
r...