Search Results for author: Raymond Chan

Found 15 papers, 2 papers with code

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

EvalCrafter: Benchmarking and Evaluating Large Video Generation Models

1 code implementation17 Oct 2023 Yaofang Liu, Xiaodong Cun, Xuebo Liu, Xintao Wang, Yong Zhang, Haoxin Chen, Yang Liu, Tieyong Zeng, Raymond Chan, Ying Shan

For video generation, various open-sourced models and public-available services have been developed to generate high-quality videos.

Benchmarking Language Modelling +4

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.

Segmentation

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 +3

Novel Sparse Recovery Algorithms for 3D Debris Localization using Rotating Point Spread Function Imagery

no code implementations27 Sep 2018 Chao Wang, Robert Plemmons, Sudhakar Prasad, Raymond Chan, Mila Nikolova

An optical imager that exploits off-center image rotation to encode both the lateral and depth coordinates of point sources in a single snapshot can perform 3D localization and tracking of space debris.

Dynamic Spectral Residual Superpixels

no code implementations10 Oct 2019 Jianchao Zhang, Angelica I. Aviles-Rivero, Daniel Heydecker, Xiaosheng Zhuang, Raymond Chan, Carola-Bibiane Schönlieb

We consider the problem of segmenting an image into superpixels in the context of $k$-means clustering, in which we wish to decompose an image into local, homogeneous regions corresponding to the underlying objects.

Clustering Superpixels

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

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

Dual-View Selective Instance Segmentation Network for Unstained Live Adherent Cells in Differential Interference Contrast Images

no code implementations27 Jan 2023 Fei Pan, Yutong Wu, Kangning Cui, Shuxun Chen, Yanfang Li, Yaofang Liu, Adnan Shakoor, Han Zhao, Beijia Lu, Shaohua Zhi, Raymond Chan, Dong Sun

In this study, we developed a novel deep-learning algorithm called dual-view selective instance segmentation network (DVSISN) for segmenting unstained adherent cells in differential interference contrast (DIC) images.

Instance Segmentation Segmentation +1

Connections between Operator-splitting Methods and Deep Neural Networks with Applications in Image Segmentation

no code implementations18 Jul 2023 Hao liu, Xue-Cheng Tai, Raymond Chan

In this paper, we give an algorithmic explanation for deep neural networks, especially in their connections with operator splitting.

Image Segmentation Semantic Segmentation

Double-well Net for Image Segmentation

no code implementations31 Dec 2023 Hao liu, Jun Liu, Raymond Chan, Xue-Cheng Tai

In this study, our goal is to integrate classical mathematical models with deep neural networks by introducing two novel deep neural network models for image segmentation known as Double-well Nets.

Image Segmentation Segmentation +1

BP-DeepONet: A new method for cuffless blood pressure estimation using the physcis-informed DeepONet

no code implementations29 Feb 2024 Lingfeng li, Xue-Cheng Tai, Raymond Chan

Unlike previous methods, our approach requires the predicted ABP waveforms to satisfy the Navier-Stokes equation with a time-periodic condition and a Windkessel boundary condition.

Blood pressure estimation Meta-Learning

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