Weiwen Chen

University of Macau

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Henry Horng‐Shing Lu

National Yang Ming Chiao Tung University

Chi‐Man Pun

University of Macau

Ling Kuo

Taipei Veterans General Hospital

Shenghong Luo

University of Macau

Chien‐Chao Tseng

National Yang Ming Chiao Tung University

Shih‐Lin Chang

Puer University

Ting‐Yung Chang

Taipei Veterans General Hospital

Jing Hu

University of Michigan–Ann Arbor

Yenn‐Jiang Lin

Taipei Veterans General Hospital

Xuesen Dong

University of British Columbia

Cooperative Institutions

National Yang Ming Chiao Tung University

Taipei Veterans General Hospital

Shandong University

National Taipei University

National Yang Ming University Hospital

Capital Medical University

Sun Yat-sen University

Guangdong Medical College

Cardiovascular Institute Hospital

Guangzhou Medical University

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UWFormer: Underwater Image Enhancement via a Semi-Supervised Multi-Scale Transformer

arXiv (Cornell University) (2023)

Xuhang Chen Zinuo Li Shenghong Luo Weiwen Chen Shuqiang Wang

Underwater images often exhibit poor quality, imbalanced coloration, and low contrast due to the complex and intricate interaction of light, water, and objects. Despite the significant contributions of previous underwater enhancement techniques, there exist several problems that demand further improvement: (i) Current deep learning methodologies depend on Convolutional Neural Networks (CNNs) that lack multi-scale enhancement and also have limited global perception fields. (ii) The scarcity of paired real-world underwater datasets poses a considerable challenge, and the utilization of synthetic image pairs risks overfitting. To address the aforementioned issues, this paper presents a Multi-scale Transformer-based Network called UWFormer for enhancing images at multiple frequencies via semi-supervised learning, in which we propose a Nonlinear Frequency-aware Attention mechanism and a Multi-Scale Fusion Feed-forward Network for low-frequency enhancement. Additionally, we introduce a specialized underwater semi-supervised training strategy, proposing a Subaqueous Perceptual Loss function to generate reliable pseudo labels. Experiments using full-reference and non-reference underwater benchmarks demonstrate that our method outperforms state-of-the-art methods in terms of both quantity and visual quality.

Overfitting

10.48550/arxiv.2310.20210

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Devignet: High-Resolution Vignetting Removal via a Dual Aggregated Fusion Transformer With Adaptive Channel Expansion

arXiv (Cornell University) (2023)

Shenghong Luo Xuhang Chen Weiwen Chen Zinuo Li Shuqiang Wang

Vignetting commonly occurs as a degradation in images resulting from factors such as lens design, improper lens hood usage, and limitations in camera sensors. This degradation affects image details, color accuracy, and presents challenges in computational photography. Existing vignetting removal algorithms predominantly rely on ideal physics assumptions and hand-crafted parameters, resulting in the ineffective removal of irregular vignetting and suboptimal results. Moreover, the substantial lack of real-world vignetting datasets hinders the objective and comprehensive evaluation of vignetting removal. To address these challenges, we present Vigset, a pioneering dataset for vignetting removal. Vigset includes 983 pairs of both vignetting and vignetting-free high-resolution ($5340\times3697$) real-world images under various conditions. In addition, We introduce DeVigNet, a novel frequency-aware Transformer architecture designed for vignetting removal. Through the Laplacian Pyramid decomposition, we propose the Dual Aggregated Fusion Transformer to handle global features and remove vignetting in the low-frequency domain. Additionally, we propose the Adaptive Channel Expansion Module to enhance details in the high-frequency domain. The experiments demonstrate that the proposed model outperforms existing state-of-the-art methods. The code, models, and dataset are available at \url{https://github.com/CXH-Research/DeVigNet}.

Vignetting

10.48550/arxiv.2308.13739

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TS-Net: a spatial–temporal entanglement model for predicting the operational status of transmission towers

Electrical Engineering (2025)

Weiwen Chen Yu Song Yilang Huang Jigang Wang Baisen Lin

Net (polyhedron)

10.1007/s00202-025-02977-0

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PO-04-183 ARTIFICIAL INTELLIGENCE-ENABLED MODEL FOR EARLY DETECTION OF ATRIAL FIBRILLATION DURING SINUS RHYTHM AND MORTALITY RISK STRATIFICATION

Heart Rhythm (2023)

Yu‐Feng Hu Chih‐Min Liu Weiwen Chen I‐Chien Wu Pei‐Fen Chen

Risk Stratification

10.1016/j.hrthm.2023.03.1294

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EDRM: A Unified Approach for Enterprise Data Resource Management

Weiwen Chen Ma Shilong

Summary Data resource always plays the key role in modern enterprise applications. In the paper, we first give a detailed introduction of the existing data resource management approaches. Via the analysis and comparison of the existing apprpaches, a new unified framework for enterprise data resource management is proposed. The framework can encapsulate the heterogeneous data resources in a universal form based on the data persistence technology, and thus provide a unified data access interface for the enterprise applications. The architecture and the main modules of the framework are detailedly introduced in the paper. And an application example is included in the end to show the usability of the framework.

Enterprise data management

Data access

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Identify Obstacles of Digestion and Absorption of Chronic Gastritis

Journal of Guangxi Normal University (2009)

Weiwen Chen

This paper mainly aims at analysis of gastrointestinal mucosa gene expression profiles of paired samples about spleen deficiency of chronic superficial gastritis and normal people group,and spleen deficiency of chronic superficial gastritis and piwei damp-heat group.9 and 12 different genes are selected by using Wilcoxon signed rank test,the ratio of quadratic sum between groups and within groups(BSS/WSS)and distance-related analysis in the process of feature selection.The forecast accuracy are 96.67% and 98.89% for two groups of data with SVM classification,which shows that the method is feasible and effective.

Chronic gastritis

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Study on the relationship between salivary amylase secretion disorder and cAMP-PKA signaling pathway in splenasthenic rat

Weiwen Chen

Objective:To comparise changes of salivary amylase secretion stimulated by acid and cAMP-PKA signaling pathway between normal and splenasthenic rat,reveals the mechanism of salivary amylase secretion disorder.Methods:The model group rats received reserpine through subcutaneous injection while the control group rats received the same volume of saline for 8 days.On the 9th and 37th days of experiment,the animal were anaesthetized and the left parotid was removed,the wounds were sutured.When the animals were awake but drowsy,20μL 10% glacial acetic acid was applied on the apex of the tongue every minutes for 30 minutes,remove the right parotid gland of the animals.the samples assayed for salivary amylase activity(sAA),cAMP、PKA activity、protein expression of VAMP8 and SNAP-23.Results:On the 9th and 37th day of experiment,sAA were not significantly different between splenasthenic and Normal groups pre acid stimulation,higher in splenasthenic groups after acid stimulation.cAMP were not significantly different between splenasthenic and Normal groups on the 9th day,lower in splenasthenic groups acid stimulated on the 37th day.Elevated levels of PKA activity was lower in splenasthenic group acid stimulated on the 9th and 37th day of experiment.VAMP-8 expression were not different between splenasthenic and normal groups,SNAP-23 expression was down regulation on the 9th and 37th day of experiment.Conclusion:Salivary amylase secretion disorder is closely related to changes of cAMP-PKA signaling pathway in Spleen deficiency rats including lower of PKA activity and SNAP-23 protein expression.

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Molecular Identification of Amomum villosum Lour.Based on Sequence Analysis of 26S rDNA D1-D3 Region and matK Gene

Guangzhou Zhongyiyao Daxue xuebao (2010)

Weiwen Chen

Objective To establish a molecular identification method for three cultivars of Amomum villosum Lour.(AVL),thus to provide scientific evidence for the identification,selection and breeding of AVL.Methods The fragments of 26S rDNA D1-D3 region and matK gene of three cultivars of AVL and Amomum longiligulare T.L.Wu were amplified by polymerase chain reaction(PCR) and with corresponding primers,and then their sequences were analyzed,and phylogenetic tree was constructed based on the sequences.Results We obtained 739 bp in 26S rDNA D1-D3 sequence.Differences in 4 basic sites of 739 bp were shown between AVL and Amomum longiligulare T.L.Wu.The two cultivars of AVL,Changguo and Yuanguo,had the same sequence,but there was a difference in one basic site of Changguo and Yuanguo from Chunxuan.The phylogenetic tree based on 26S rDNA D1-D3 sequence revealed the difference between Chunxuan and the other two cultivars of AVL.We also obtained 824 bp in matK gene sequence.The three cultivars of AVL showed the consistent sequence,but there was a difference in one basic site of three cultivars of AVL from Amomum longiligulare T.L.Wu.Conclusion We can identify the three cultivars of AVL through the sequence differences at the molecular level,and Chunxuan has a closer genetic relationship with Amomum longiligulare T.L.Wu.

Sequence (biology)

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Supplementary Data from KIF15-Mediated Stabilization of AR and AR-V7 Contributes to Enzalutamide Resistance in Prostate Cancer

Lin Gao Wei Zhang Jing Zhang Junmei Liu Feifei Sun

<p>Supplemental Materials and Methods</p>

Enzalutamide

10.1158/0008-5472.22427617

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[Comparative Study on Effects of Anti-contusion Injury, Analgesia and Anti-inflammation of Root and Stem of Zanthoxylum nitidum].

PubMed (2015)

Wei-xuan Chen Ze-hui Qin Dan Zeng Zhengzhou Han Ruo-ting Zhan

To provide the scientific evidence for expansion of medicinal parts of Zanthoxylum nitidum by comparing the effects of anti-contusion injury, analgesia and anti-inflammation of its root and stem.The pharmacological effects between root and stem of Zanthoxylum nitidum were compared by observing the anti-injury effect in rats with injury struck by hammer. The analgesic effect in mice was evaluated by writhing test and hot plate test, and the anti-inflammatory effect on paw edema induced by carrageenan and granuloma induced by cotton pellet were investigated in rats.Both root and stem of Zanthoxylum nitidum relieved the exterior and histological symptoms of rats' injury legs struck by hammer, decreased the numbers of mice's writhing, enhanced pain threshold of mice on heat plate, inhibited the edema of rats induced by carrageenan, and suppressed the granuloma of rats induced by cotton pellet.Stem of Zanthoxylum nitidum has similar effects of anti-contusion injury, analgesia and anti-inflammation with root of Zanthoxylum nitidum.

Zanthoxylum

Carrageenan

Soft tissue injury

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Citations (8)