940 citations · 2k across the 39 of their papers we have counts for
8 papers · 1 filter
Vision-based Teleoperation of Shadow Dexterous Hand using End-to-End Deep Neural Network
Shuang Li, Xiaojian Ma, Hongzhuo Liang +5
In this paper, we present TeachNet, a novel neural network architecture for intuitive and markerless vision-based teleoperation of dexterous robotic hands. Robot joint angles are d…
PointNetGPD: Detecting Grasp Configurations from Point Sets
Hongzhuo Liang, Xiaojian Ma, Shuang Li +5
In this paper, we propose an end-to-end grasp evaluation model to address the challenging problem of localizing robot grasp configurations directly from the point cloud. Compared t…
Deep Feature Pyramid Reconfiguration for Object Detection
Tao Kong, Fuchun Sun, Wenbing Huang +1
State-of-the-art object detectors usually learn multi-scale representations to get better results by employing feature pyramids. However, the current designs for feature pyramids a…
Spatial and Spectral Features Fusion for EEG Classification during Motor Imagery in BCI
Chuanqi Tan, Fuchun Sun, Wenchang Zhang +2
Brain computer interface (BCI) is the only way for some special patients to communicate with the outside world and provide a direct control channel between brain and the external d…
A Survey on Deep Transfer Learning
Chuanqi Tan, Fuchun Sun, Tao Kong +3
As a new classification platform, deep learning has recently received increasing attention from researchers and has been successfully applied to many domains. In some domains, like…
Deep Transfer Learning for EEG-based Brain Computer Interface
Chuanqi Tan, Fuchun Sun, Wenchang Zhang
The electroencephalography classifier is the most important component of brain-computer interface based systems. There are two major problems hindering the improvement of it. First…
Multimodal Classification with Deep Convolutional-Recurrent Neural Networks for Electroencephalography
Chuanqi Tan, Fuchun Sun, Wenchang Zhang +2
Electroencephalography (EEG) has become the most significant input signal for brain computer interface (BCI) based systems. However, it is very difficult to obtain satisfactory cla…
Learning and Inferring Movement with Deep Generative Model
Mingxuan Jing, Xiaojian Ma, Fuchun Sun +1
Learning and inference movement is a very challenging problem due to its high dimensionality and dependency to varied environments or tasks. In this paper, we propose an effective…