Search Results for author: Fei Chen

Found 41 papers, 11 papers with code

Accelerating Diffusion Sampling with Optimized Time Steps

no code implementations27 Feb 2024 Shuchen Xue, Zhaoqiang Liu, Fei Chen, Shifeng Zhang, Tianyang Hu, Enze Xie, Zhenguo Li

While this is a significant development, most sampling methods still employ uniform time steps, which is not optimal when using a small number of steps.

Image Generation

TAnet: A New Temporal Attention Network for EEG-based Auditory Spatial Attention Decoding with a Short Decision Window

no code implementations11 Jan 2024 Yuting Ding, Fei Chen

Auditory spatial attention detection (ASAD) is used to determine the direction of a listener's attention to a speaker by analyzing her/his electroencephalographic (EEG) signals.

EEG

On Topological Conditions for Enabling Transient Control in Leader-follower Networks

no code implementations6 Dec 2023 Fei Chen, Dimos V. Dimarogonas

We derive necessary and sufficient conditions for leader-follower multi-agent systems such that we can further apply prescribed performance control to achieve the desired formation while satisfying certain transient constraints.

BiRP: Learning Robot Generalized Bimanual Coordination using Relative Parameterization Method on Human Demonstration

1 code implementation12 Jul 2023 Junjia Liu, Hengyi Sim, Chenzui Li, Fei Chen

We demonstrate the method using synthetic motions and human demonstration data and deploy it to a humanoid robot to perform a generalized bimanual coordination motion.

Data Augmentation

SoftGPT: Learn Goal-oriented Soft Object Manipulation Skills by Generative Pre-trained Heterogeneous Graph Transformer

1 code implementation22 Jun 2023 Junjia Liu, Zhihao LI, WanYu Lin, Sylvain Calinon, Kay Chen Tan, Fei Chen

Soft object manipulation tasks in domestic scenes pose a significant challenge for existing robotic skill learning techniques due to their complex dynamics and variable shape characteristics.

Object

Calibrationless Reconstruction of Uniformly-Undersampled Multi-Channel MR Data with Deep Learning Estimated ESPIRiT Maps

no code implementations26 Oct 2022 Junhao Zhang, Zheyuan Yi, Yujiao Zhao, Linfang Xiao, Jiahao Hu, Christopher Man, Vick Lau, Shi Su, Fei Chen, Alex T. L. Leong, Ed X. Wu

Further, they led to excellent ESPIRiT reconstruction performance even at high acceleration, exhibiting a similar level of errors and artifacts to that by using reference ESPIRiT maps.

Dual-Curriculum Teacher for Domain-Inconsistent Object Detection in Autonomous Driving

no code implementations17 Oct 2022 Longhui Yu, Yifan Zhang, Lanqing Hong, Fei Chen, Zhenguo Li

Specifically, DucTeacher consists of two curriculums, i. e., (1) domain evolving curriculum seeks to learn from the data progressively to handle data distribution discrepancy by estimating the similarity between domains, and (2) distribution matching curriculum seeks to estimate the class distribution for each unlabeled domain to handle class distribution shifts.

Autonomous Driving object-detection +2

6DOF Pose Estimation of a 3D Rigid Object based on Edge-enhanced Point Pair Features

no code implementations17 Sep 2022 Chenyi Liu, Fei Chen, Lu Deng, Renjiao Yi, Lintao Zheng, Chenyang Zhu, Jia Wang, Kai Xu

We introduce a well-targeted down-sampling strategy that focuses more on edge area for efficient feature extraction of complex geometry.

6D Pose Estimation

A Consistency Constraint-Based Approach to Coupled State Constraints in Distributed Model Predictive Control

no code implementations24 Aug 2022 Adrian Wiltz, Fei Chen, Dimos V. Dimarogonas

In this paper, we present a distributed model predictive control (DMPC) scheme for dynamically decoupled systems which are subject to state constraints, coupling state constraints and input constraints.

Model Predictive Control

Less is More: Adaptive Curriculum Learning for Thyroid Nodule Diagnosis

1 code implementation2 Jul 2022 Haifan Gong, Hui Cheng, Yifan Xie, Shuangyi Tan, Guanqi Chen, Fei Chen, Guanbin Li

Thyroid nodule classification aims at determining whether the nodule is benign or malignant based on a given ultrasound image.

Classification

Manifold Graph Signal Restoration using Gradient Graph Laplacian Regularizer

no code implementations9 Jun 2022 Fei Chen, Gene Cheung, Xue Zhang

In this paper, focusing on manifold graphs -- collections of uniform discrete samples on low-dimensional continuous manifolds -- we generalize GLR to gradient graph Laplacian regularizer (GGLR) that promotes planar / piecewise planar (PWP) signal reconstruction.

Graph Embedding

XBound-Former: Toward Cross-scale Boundary Modeling in Transformers

1 code implementation2 Jun 2022 Jiacheng Wang, Fei Chen, Yuxi Ma, Liansheng Wang, Zhaodong Fei, Jianwei Shuai, Xiangdong Tang, Qichao Zhou, Jing Qin

Skin lesion segmentation from dermoscopy images is of great significance in the quantitative analysis of skin cancers, which is yet challenging even for dermatologists due to the inherent issues, i. e., considerable size, shape and color variation, and ambiguous boundaries.

Lesion Segmentation Segmentation +1

MBI-Net: A Non-Intrusive Multi-Branched Speech Intelligibility Prediction Model for Hearing Aids

no code implementations7 Apr 2022 Ryandhimas E. Zezario, Fei Chen, Chiou-Shann Fuh, Hsin-Min Wang, Yu Tsao

In this study, we propose a multi-branched speech intelligibility prediction model (MBI-Net), for predicting the subjective intelligibility scores of HA users.

Fast Computation of Generalized Eigenvectors for Manifold Graph Embedding

no code implementations15 Dec 2021 Fei Chen, Gene Cheung, Xue Zhang

Experiments show that our embedding is among the fastest in the literature, while producing the best clustering performance for manifold graphs.

Clustering Graph Embedding

Deep Learning-based Non-Intrusive Multi-Objective Speech Assessment Model with Cross-Domain Features

1 code implementation3 Nov 2021 Ryandhimas E. Zezario, Szu-Wei Fu, Fei Chen, Chiou-Shann Fuh, Hsin-Min Wang, Yu Tsao

In this study, we propose a cross-domain multi-objective speech assessment model called MOSA-Net, which can estimate multiple speech assessment metrics simultaneously.

Speech Enhancement

Learning Robotic Ultrasound Scanning Skills via Human Demonstrations and Guided Explorations

no code implementations2 Nov 2021 Xutian Deng, Yiting Chen, Fei Chen, Miao Li

Medical ultrasound has become a routine examination approach nowadays and is widely adopted for different medical applications, so it is desired to have a robotic ultrasound system to perform the ultrasound scanning autonomously.

Imitation Learning

LV-BERT: Exploiting Layer Variety for BERT

1 code implementation Findings (ACL) 2021 Weihao Yu, Zihang Jiang, Fei Chen, Qibin Hou, Jiashi Feng

In this paper, beyond this stereotyped layer pattern, we aim to improve pre-trained models by exploiting layer variety from two aspects: the layer type set and the layer order.

No Fear of Heterogeneity: Classifier Calibration for Federated Learning with Non-IID Data

1 code implementation NeurIPS 2021 Mi Luo, Fei Chen, Dapeng Hu, Yifan Zhang, Jian Liang, Jiashi Feng

Motivated by the above findings, we propose a novel and simple algorithm called Classifier Calibration with Virtual Representations (CCVR), which adjusts the classifier using virtual representations sampled from an approximated gaussian mixture model.

Classifier calibration Federated Learning

Whole-Body Control on Non-holonomic Mobile Manipulation for Grapevine Winter Pruning Automation

no code implementations22 May 2021 Tao Teng, Miguel Fernandes, Matteo Gatti, Stefano Poni, Claudio Semini, Darwin Caldwell, Fei Chen

In this paper, we explore a whole-body motion controller of a robot which is composed of a 2-DoFs non-holonomic wheeled mobile base with a 7-DoFs manipulator (non-holonomic wheeled mobile manipulator, NWMM) This robotic platform is designed to efficiently undertake complex grapevine pruning tasks.

Two stages for visual object tracking

no code implementations28 Apr 2021 Fei Chen, Fuhan Zhang, Xiaodong Wang

Then more accurate tracking results are obtained by segmentation module given the coarse state estimation in the first stage.

Image Segmentation Object +4

Intuitive Tasks Planning Using Visuo-Tactile Perception for Human Robot Cooperation

no code implementations1 Apr 2021 Sunny Katyara, Fanny Ficuciello, Tao Teng, Fei Chen, Bruno Siciliano, Darwin G. Caldwell

Designing robotic tasks for co-manipulation necessitates to exploit not only proprioceptive but also exteroceptive information for improved safety and autonomy.

The effect of speech and noise levels on the quality perceived by cochlear implant and normal hearing listeners

no code implementations3 Mar 2021 Sara Akbarzadeh, Sungmin Lee, Fei Chen, Chin-Tuan Tan

Noise reduction (NR) algorithms used in CI reduce the noise in favor of signal-to-noise ratio (SNR), regardless of plausible accompanying distortions that may degrade the speech quality perception.

Fast & Robust Image Interpolation using Gradient Graph Laplacian Regularizer

no code implementations25 Jan 2021 Fei Chen, Gene Cheung, Xue Zhang

In the graph signal processing (GSP) literature, it has been shown that signal-dependent graph Laplacian regularizer (GLR) can efficiently promote piecewise constant (PWC) signal reconstruction for various image restoration tasks.

Image Restoration

Reproducible Pruning System on Dynamic Natural Plants for Field Agricultural Robots

no code implementations26 Aug 2020 Sunny Katyara, Fanny Ficuciello, Darwin G. Caldwell, Fei Chen, Bruno Siciliano

The Natural Admittance Controller (NAC) is applied to deal with the dynamics of vines.

Robotics Systems and Control Systems and Control

Risk Variance Penalization

no code implementations13 Jun 2020 Chuanlong Xie, Haotian Ye, Fei Chen, Yue Liu, Rui Sun, Zhenguo Li

The key of the out-of-distribution (OOD) generalization is to generalize invariance from training domains to target domains.

MetaSelector: Meta-Learning for Recommendation with User-Level Adaptive Model Selection

no code implementations22 Jan 2020 Mi Luo, Fei Chen, Pengxiang Cheng, Zhenhua Dong, Xiuqiang He, Jiashi Feng, Zhenguo Li

Recommender systems often face heterogeneous datasets containing highly personalized historical data of users, where no single model could give the best recommendation for every user.

Meta-Learning Model Selection +1

Dynamic Spatio-temporal Graph-based CNNs for Traffic Prediction

no code implementations5 Dec 2018 Ken Chen, Fei Chen, Baisheng Lai, Zhongming Jin, Yong liu, Kai Li, Long Wei, Pengfei Wang, Yandong Tang, Jianqiang Huang, Xian-Sheng Hua

To capture the graph dynamics, we use the graph prediction stream to predict the dynamic graph structures, and the predicted structures are fed into the flow prediction stream.

Traffic Prediction

Federated Meta-Learning with Fast Convergence and Efficient Communication

1 code implementation22 Feb 2018 Fei Chen, Mi Luo, Zhenhua Dong, Zhenguo Li, Xiuqiang He

Statistical and systematic challenges in collaboratively training machine learning models across distributed networks of mobile devices have been the bottlenecks in the real-world application of federated learning.

Federated Learning Meta-Learning +1

Real-Time Localization and Tracking of Multiple Radio-Tagged Animals with an Autonomous UAV

1 code implementation5 Dec 2017 Hoa Van Nguyen, Michael Chesser, Fei Chen, S. Hamid Rezatofighi, Damith C. Ranasinghe

Autonomous aerial robots provide new possibilities to study the habitats and behaviors of endangered species through the efficient gathering of location information at temporal and spatial granularities not possible with traditional manual survey methods.

Systems and Control Robotics

Meta-SGD: Learning to Learn Quickly for Few-Shot Learning

9 code implementations31 Jul 2017 Zhenguo Li, Fengwei Zhou, Fei Chen, Hang Li

In contrast, meta-learning learns from many related tasks a meta-learner that can learn a new task more accurately and faster with fewer examples, where the choice of meta-learners is crucial.

Few-Shot Learning reinforcement-learning +1

External Patch Prior Guided Internal Clustering for Image Denoising

no code implementations ICCV 2015 Fei Chen, Lei Zhang, Huimin Yu

One category of denoising methods exploit the priors (e. g., TV, sparsity) learned from external clean images to reconstruct the given noisy image, while another category of methods exploit the internal prior (e. g., self-similarity) to reconstruct the latent image.

Clustering Image Denoising

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