Search Results for author: Tieyong Zeng

Found 38 papers, 12 papers with code

DSFNet: Convolutional Encoder-Decoder Architecture Combined Dual-GCN and Stand-alone Self-attention by Fast Normalized Fusion for Polyps Segmentation

1 code implementation15 Aug 2023 Juntong Fan, Tieyong Zeng, Dayang Wang

In the past few decades, deep learning technology has been widely used in medical image segmentation and has made significant breakthroughs in the fields of liver and liver tumor segmentation, brain and brain tumor segmentation, video disc segmentation, heart image segmentation, and so on.

Brain Tumor Segmentation Image Segmentation +1

Rethink Depth Separation with Intra-layer Links

no code implementations11 May 2023 Feng-Lei Fan, Ze-Yu Li, Huan Xiong, Tieyong Zeng

Then, we modify the depth separation theory by showing that a shallow network with intra-layer links does not need to go as wide as before to express some hard functions constructed by a deep network.

Recognizable Information Bottleneck

1 code implementation28 Apr 2023 Yilin Lyu, Xin Liu, Mingyang Song, Xinyue Wang, Yaxin Peng, Tieyong Zeng, Liping Jing

The recent PAC-Bayes IB uses information complexity instead of information compression to establish a connection with the mutual information generalization bound.

Fast MRI Reconstruction via Edge Attention

1 code implementation22 Apr 2023 Hanhui Yang, Juncheng Li, Lok Ming Lui, Shihui Ying, Jun Shi, Tieyong Zeng

To solve this problem, we propose a lightweight and accurate Edge Attention MRI Reconstruction Network (EAMRI) to reconstruct images with edge guidance.

MRI Reconstruction

EWT: Efficient Wavelet-Transformer for Single Image Denoising

no code implementations13 Apr 2023 Juncheng Li, Bodong Cheng, Ying Chen, Guangwei Gao, Tieyong Zeng

Transformer-based image denoising methods have achieved encouraging results in the past year.

Image Denoising

Randomly Projected Convex Clustering Model: Motivation, Realization, and Cluster Recovery Guarantees

no code implementations29 Mar 2023 Ziwen Wang, Yancheng Yuan, Jiaming Ma, Tieyong Zeng, Defeng Sun

In this paper, we propose a randomly projected convex clustering model for clustering a collection of $n$ high dimensional data points in $\mathbb{R}^d$ with $K$ hidden clusters.


PFT-SSR: Parallax Fusion Transformer for Stereo Image Super-Resolution

no code implementations24 Mar 2023 Hansheng Guo, Juncheng Li, Guangwei Gao, Zhi Li, Tieyong Zeng

Stereo image super-resolution aims to boost the performance of image super-resolution by exploiting the supplementary information provided by binocular systems.

Stereo Image Super-Resolution

One Neuron Saved Is One Neuron Earned: On Parametric Efficiency of Quadratic Networks

1 code implementation11 Mar 2023 Feng-Lei Fan, Hang-Cheng Dong, Zhongming Wu, Lecheng Ruan, Tieyong Zeng, Yiming Cui, Jing-Xiao Liao

In this paper, with theoretical and empirical studies, we show that quadratic networks enjoy parametric efficiency, thereby confirming that the superior performance of quadratic networks is due to the intrinsic expressive capability.

Multi-Prototypes Convex Merging Based K-Means Clustering Algorithm

no code implementations14 Feb 2023 Dong Li, Shuisheng Zhou, Tieyong Zeng, Raymond H. Chan

Specifically, CM can obtain the optimal merging and estimate the correct k. By integrating these two techniques with K-Means algorithm, the proposed MCKM is an efficient and explainable clustering algorithm for escaping the undesirable local minima of K-Means problem without given k first.


Hierarchical Perception Adversarial Learning Framework for Compressed Sensing MRI

no code implementations27 Jan 2023 Zhifan Gao, Yifeng Guo, Jiajing Zhang, Tieyong Zeng, Guang Yang

HP-ALF can perceive the image information in the hierarchical mechanism: image-level perception and patch-level perception.

Towards NeuroAI: Introducing Neuronal Diversity into Artificial Neural Networks

no code implementations23 Jan 2023 Feng-Lei Fan, Yingxin Li, Hanchuan Peng, Tieyong Zeng, Fei Wang

In the human brain, neuronal diversity is an enabling factor for all kinds of biological intelligent behaviors.

ACTIVE: A Deep Model for Sperm and Impurity Detection in Microscopic Videos

no code implementations15 Jan 2023 Ao Chen, Jinghua Zhang, Md Mamunur Rahaman, Hongzan Sun, M. D., Tieyong Zeng, Marcin Grzegorzek, Feng-Lei Fan, Chen Li

The accurate detection of sperms and impurities is a very challenging task, facing problems such as the small size of targets, indefinite target morphologies, low contrast and resolution of the video, and similarity of sperms and impurities.

object-detection Object Detection

Retinex Image Enhancement Based on Sequential Decomposition With a Plug-and-Play Framework

no code implementations11 Oct 2022 Tingting Wu, Wenna Wu, Ying Yang, Feng-Lei Fan, Tieyong Zeng

In this paper, using a sequential Retinex decomposition strategy, we design a plug-and-play framework based on the Retinex theory for simultaneously image enhancement and noise removal.

Denoising Low-Light Image Enhancement

Uncertainty-Aware Unsupervised Image Deblurring with Deep Residual Prior

no code implementations CVPR 2023 Xiaole Tang, XiLe Zhao, Jun Liu, Jianli Wang, Yuchun Miao, Tieyong Zeng

To address this challenge, we suggest a dataset-free deep residual prior for the kernel induced error (termed as residual) expressed by a customized untrained deep neural network, which allows us to flexibly adapt to different blurs and images in real scenarios.

Deblurring Image Deblurring

Spherical Image Inpainting with Frame Transformation and Data-driven Prior Deep Networks

no code implementations29 Sep 2022 Jianfei Li, Chaoyan Huang, Raymond Chan, Han Feng, Micheal Ng, Tieyong Zeng

Spherical image processing has been widely applied in many important fields, such as omnidirectional vision for autonomous cars, global climate modelling, and medical imaging.

Image Inpainting

Snow Mask Guided Adaptive Residual Network for Image Snow Removal

no code implementations11 Jul 2022 Bodong Cheng, Juncheng Li, Ying Chen, Shuyi Zhang, Tieyong Zeng

Recently, some methods have been proposed for snow removing, and most methods deal with snow images directly as the optimization object.

Image Restoration object-detection +4

A hybrid data driven-physics constrained Gaussian process regression framework with deep kernel for uncertainty quantification

no code implementations13 May 2022 Cheng Chang, Tieyong Zeng

The proposed model learns from both data and physics constraints through the training of a deep neural network, which serves as part of the covariance function in GPR.

GPR regression

Convex Augmentation for Total Variation Based Phase Retrieval

no code implementations21 Apr 2022 Jianwei Niu, Hok Shing Wong, Tieyong Zeng

Phase retrieval is an important problem with significant physical and industrial applications.


A Survey on Epistemic (Model) Uncertainty in Supervised Learning: Recent Advances and Applications

no code implementations3 Nov 2021 Xinlei Zhou, Han Liu, Farhad Pourpanah, Tieyong Zeng, XiZhao Wang

This paper provides a comprehensive review of epistemic uncertainty learning techniques in supervised learning over the last five years.

From Beginner to Master: A Survey for Deep Learning-based Single-Image Super-Resolution

1 code implementation29 Sep 2021 Juncheng Li, Zehua Pei, Tieyong Zeng

In this survey, we give an overview of DL-based SISR methods and group them according to their targets, such as reconstruction efficiency, reconstruction accuracy, and perceptual accuracy.

Image Quality Assessment Image Super-Resolution

Transformer for Single Image Super-Resolution

1 code implementation25 Aug 2021 Zhisheng Lu, Juncheng Li, Hong Liu, Chaoyan Huang, Linlin Zhang, Tieyong Zeng

LTB is composed of a series of Efficient Transformers (ET), which occupies a small GPU memory occupation, thanks to the specially designed Efficient Multi-Head Attention (EMHA).

Image Super-Resolution

Structure-Preserving Deraining with Residue Channel Prior Guidance

1 code implementation ICCV 2021 Qiaosi Yi, Juncheng Li, Qinyan Dai, Faming Fang, Guixu Zhang, Tieyong Zeng

Although these methods can remove part of the rain streaks, it is difficult for them to adapt to real-world scenarios and restore high-quality rain-free images with clear and accurate structures.

Single Image Deraining

Rank-One Prior: Toward Real-Time Scene Recovery

no code implementations CVPR 2021 Jun Liu, Ryan Wen Liu, Jianing Sun, Tieyong Zeng

To improve visual quality under different weather/imaging conditions, we propose a real-time light correction method to recover the degraded scenes in the cases of sandstorms, underwater, and haze.

Autonomous Vehicles

A deep neural network approach on solving the linear transport model under diffusive scaling

no code implementations24 Feb 2021 Liu Liu, Tieyong Zeng, Zecheng Zhang

In our framework, the solution is approximated by a neural network that satisfies both the governing equation and other constraints.

Numerical Analysis Numerical Analysis

Edge Adaptive Hybrid Regularization Model For Image Deblurring

no code implementations20 Nov 2020 Tingting Zhang, Jie Chen, Caiying Wu, Zhifei He, Tieyong Zeng, Qiyu Jin

In the proposed model, it detects the edges and then spatially adjusts the parameters of Tikhonov and TV regularization terms for each pixel according to the edge information.

Deblurring Image Deblurring +2

Deep Tensor CCA for Multi-view Learning

1 code implementation25 May 2020 Hok Shing Wong, Li Wang, Raymond Chan, Tieyong Zeng

We present Deep Tensor Canonical Correlation Analysis (DTCCA), a method to learn complex nonlinear transformations of multiple views (more than two) of data such that the resulting representations are linearly correlated in high order.

MULTI-VIEW LEARNING Tensor Decomposition

Large-Scale Semi-Supervised Learning via Graph Structure Learning over High-Dense Points

no code implementations4 Dec 2019 Zitong Wang, Li Wang, Raymond Chan, Tieyong Zeng

A novel approach is then proposed to construct the graph of the input data from the learned graph of a small number of vertexes with some preferred properties.

Graph structure learning

Linkage between piecewise constant Mumford-Shah model and ROF model and its virtue in image segmentation

no code implementations26 Jul 2018 Xiaohao Cai, Raymond Chan, Carola-Bibiane Schonlieb, Gabriele Steidl, Tieyong Zeng

The piecewise constant Mumford-Shah (PCMS) model and the Rudin-Osher-Fatemi (ROF) model are two important variational models in image segmentation and image restoration, respectively.

Image Restoration Image Segmentation +1

A Three-stage Approach for Segmenting Degraded Color Images: Smoothing, Lifting and Thresholding (SLaT)

no code implementations30 May 2015 Xiaohao Cai, Raymond Chan, Mila Nikolova, Tieyong Zeng

In this paper, we propose a SLaT (Smoothing, Lifting and Thresholding) method with three stages for multiphase segmentation of color images corrupted by different degradations: noise, information loss, and blur.

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