Search Results for author: Qiong Liu

Found 22 papers, 11 papers with code

TAI-GAN: Temporally and Anatomically Informed GAN for early-to-late frame conversion in dynamic cardiac PET motion correction

1 code implementation23 Aug 2023 Xueqi Guo, Luyao Shi, Xiongchao Chen, Bo Zhou, Qiong Liu, Huidong Xie, Yi-Hwa Liu, Richard Palyo, Edward J. Miller, Albert J. Sinusas, Bruce Spottiswoode, Chi Liu, Nicha C. Dvornek

The rapid tracer kinetics of rubidium-82 ($^{82}$Rb) and high variation of cross-frame distribution in dynamic cardiac positron emission tomography (PET) raise significant challenges for inter-frame motion correction, particularly for the early frames where conventional intensity-based image registration techniques are not applicable.

Image Registration Motion Estimation

Masked Spatio-Temporal Structure Prediction for Self-supervised Learning on Point Cloud Videos

1 code implementation18 Aug 2023 Zhiqiang Shen, Xiaoxiao Sheng, Hehe Fan, Longguang Wang, Yulan Guo, Qiong Liu, Hao Wen, Xi Zhou

In this paper, we propose a Masked Spatio-Temporal Structure Prediction (MaST-Pre) method to capture the structure of point cloud videos without human annotations.

Self-Supervised Learning Video Understanding

Distributed Decisions on Optimal Load Balancing in Loss Networks

no code implementations10 Jul 2023 Qiong Liu, Chehao Wang, Ce Zheng

When multiple users share a common link in direct transmission, packet loss and network collision may occur due to the simultaneous arrival of traffics at the source node.

All in One: Exploring Unified Vision-Language Tracking with Multi-Modal Alignment

no code implementations7 Jul 2023 Chunhui Zhang, Xin Sun, Li Liu, Yiqian Yang, Qiong Liu, Xi Zhou, Yanfeng Wang

This approach achieves feature integration in a unified backbone, removing the need for carefully-designed fusion modules and resulting in a more effective and efficient VL tracking framework.

Three-way Imbalanced Learning based on Fuzzy Twin SVM

no code implementations19 May 2023 Wanting Cai, Mingjie Cai, Qingguo Li, Qiong Liu

Three-way decision (3WD) is a powerful tool for granular computing to deal with uncertain data, commonly used in information systems, decision-making, and medical care.

Binary Classification Decision Making +1

Cross-domain Iterative Network for Simultaneous Denoising, Limited-angle Reconstruction, and Attenuation Correction of Low-dose Cardiac SPECT

no code implementations17 May 2023 Xiongchao Chen, Bo Zhou, Huidong Xie, Xueqi Guo, Qiong Liu, Albert J. Sinusas, Chi Liu

Additionally, computed tomography (CT)-derived attenuation maps ($\mu$-maps) are commonly used for SPECT attenuation correction (AC), but it will cause extra radiation exposure and SPECT-CT misalignments.

Computed Tomography (CT) Denoising

Joint Denoising and Few-angle Reconstruction for Low-dose Cardiac SPECT Using a Dual-domain Iterative Network with Adaptive Data Consistency

no code implementations17 May 2023 Xiongchao Chen, Bo Zhou, Huidong Xie, Xueqi Guo, Qiong Liu, Albert J. Sinusas, Chi Liu

To overcome these challenges, we propose a dual-domain iterative network for end-to-end joint denoising and reconstruction from low-dose and few-angle projections of cardiac SPECT.

Denoising

PointCMP: Contrastive Mask Prediction for Self-supervised Learning on Point Cloud Videos

1 code implementation CVPR 2023 Zhiqiang Shen, Xiaoxiao Sheng, Longguang Wang, Yulan Guo, Qiong Liu, Xi Zhou

Self-supervised learning can extract representations of good quality from solely unlabeled data, which is appealing for point cloud videos due to their high labelling cost.

Self-Supervised Learning Transfer Learning

Unified Noise-aware Network for Low-count PET Denoising

no code implementations28 Apr 2023 Huidong Xie, Qiong Liu, Bo Zhou, Xiongchao Chen, Xueqi Guo, Chi Liu

To obtain optimal denoised results, we may need to train multiple networks using data with different noise levels.

Denoising

FedFTN: Personalized Federated Learning with Deep Feature Transformation Network for Multi-institutional Low-count PET Denoising

1 code implementation2 Apr 2023 Bo Zhou, Huidong Xie, Qiong Liu, Xiongchao Chen, Xueqi Guo, Zhicheng Feng, S. Kevin Zhou, Biao Li, Axel Rominger, Kuangyu Shi, James S. Duncan, Chi Liu

While previous federated learning (FL) algorithms enable multi-institution collaborative training without the need of aggregating local data, addressing the large domain shift in the application of multi-institutional low-count PET denoising remains a challenge and is still highly under-explored.

Denoising Personalized Federated Learning

HiCo: Hierarchical Contrastive Learning for Ultrasound Video Model Pretraining

1 code implementation10 Oct 2022 Chunhui Zhang, Yixiong Chen, Li Liu, Qiong Liu, Xi Zhou

This work proposes a hierarchical contrastive learning (HiCo) method to improve the transferability for the US video model pretraining.

Contrastive Learning

Reducing Action Space: Reference-Model-Assisted Deep Reinforcement Learning for Inverter-based Volt-Var Control

no code implementations10 Oct 2022 Qiong Liu, Ye Guo, Lirong Deng, Haotian Liu, Dongyu Li, Hongbin Sun

We investigate that a large action space increases the learning difficulties of DRL and degrades the optimization performance in the process of generating data and training neural networks.

You Need to Read Again: Multi-granularity Perception Network for Moment Retrieval in Videos

1 code implementation25 May 2022 Xin Sun, Xuan Wang, Jialin Gao, Qiong Liu, Xi Zhou

Moment retrieval in videos is a challenging task that aims to retrieve the most relevant video moment in an untrimmed video given a sentence description.

Moment Retrieval Reading Comprehension +1

Reducing Learning Difficulties: One-Step Two-Critic Deep Reinforcement Learning for Inverter-based Volt-Var Control

no code implementations30 Mar 2022 Qiong Liu, Ye Guo, Lirong Deng, Haotian Liu, Dongyu Li, Hongbin Sun, Wenqi Huang

Then we design the one-step actor-critic DRL scheme which is a simplified version of recent DRL algorithms, and it avoids the issue of Q value overestimation successfully.

ELSA: Enhanced Local Self-Attention for Vision Transformer

1 code implementation23 Dec 2021 Jingkai Zhou, Pichao Wang, Fan Wang, Qiong Liu, Hao Li, Rong Jin

Self-attention is powerful in modeling long-range dependencies, but it is weak in local finer-level feature learning.

Image Classification Instance Segmentation +2

Varifocal Multiview Images: Capturing and Visual Tasks

1 code implementation19 Nov 2021 Kejun Wu, Qiong Liu, Guoan Li, Gangyi Jiang, You Yang

To overcome the limitation of multiview images on visual tasks, in this paper, we present varifocal multiview (VFMV) images with flexible DoF.

Decoupled Dynamic Filter Networks

1 code implementation CVPR 2021 Jingkai Zhou, Varun Jampani, Zhixiong Pi, Qiong Liu, Ming-Hsuan Yang

Inspired by recent advances in attention, DDF decouples a depth-wise dynamic filter into spatial and channel dynamic filters.

Image Classification Semantic Segmentation

FREA-Unet: Frequency-aware U-net for Modality Transfer

no code implementations31 Dec 2020 Hajar Emami, Qiong Liu, Ming Dong

While Positron emission tomography (PET) imaging has been widely used in diagnosis of number of diseases, it has costly acquisition process which involves radiation exposure to patients.

Image Generation

Using Sensory Time-cue to enable Unsupervised Multimodal Meta-learning

no code implementations16 Sep 2020 Qiong Liu, Yanxia Zhang

As data from IoT (Internet of Things) sensors become ubiquitous, state-of-the-art machine learning algorithms face many challenges on directly using sensor data.

Meta-Learning

Adaptive Feedforward Neural Network Control with an Optimized Hidden Node Distribution

1 code implementation23 May 2020 Qiong Liu, Dongyu Li, Shuzhi Sam Ge, Zhong Ouyang

Composite adaptive radial basis function neural network (RBFNN) control with a lattice distribution of hidden nodes has three inherent demerits: 1) the approximation domain of adaptive RBFNNs is difficult to be determined a priori; 2) only a partial persistence of excitation (PE) condition can be guaranteed; and 3) in general, the required number of hidden nodes of RBFNNs is enormous.

Learning Theory

Local Feature Descriptor Learning with Adaptive Siamese Network

no code implementations16 Jun 2017 Chong Huang, Qiong Liu, Yan-Ying Chen, Kwang-Ting, Cheng

Although the recent progress in the deep neural network has led to the development of learnable local feature descriptors, there is no explicit answer for estimation of the necessary size of a neural network.

Patch Matching

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