Weiqing Yan

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DSANet-KD: Dual Semantic Approximation Network via Knowledge Distillation for Rail Surface Defect Detection
- Wujie Zhou
  School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou, China
  ,
- Jiankang Hong
  School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou, China
  ,
- Xiaoxiao Ran
  5G Innovation Center, COMAC Shanghai Aircraft Manufacturing Company Ltd., Shanghai, China
  ,
- Weiqing Yan
  School of Computer Science and Engineering, Nanyang Technological University, Jurong West, Singapore
  ,
- Qiuping Jiang
  School of Information Science and Engineering, Ningbo University, Ningbo, China
IEEE Transactions on Intelligent Transportation Systems, Volume 25, Issue 10•Oct. 2024, pp 13849-13862 • https://doi.org/10.1109/TITS.2024.3385744
Owing to the development of convolutional neural networks (CNNs), the detection of defects on rail surfaces has significantly improved. Although existing methods achieve good results, they incur huge computational and parameter costs associated with CNNs. ...
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CAGNet: Coordinated attention guidance network for RGB-T crowd counting
- Xun Yang
  School of Information and Electronic Engineering, Zhejiang University of Science & Technology, Hangzhou 310023, China
  ,
- Wujie Zhou
  School of Information and Electronic Engineering, Zhejiang University of Science & Technology, Hangzhou 310023, China
  School of Computer Science and Engineering, Nanyang Technological University, Singapore 308232, Singapore
  ,
- Weiqing Yan
  School of Computer Science and Engineering, Nanyang Technological University, Singapore 308232, Singapore
  School of Computer and Control Engineering, Yantai University, Yantai 264005, China
  ,
- Xiaohong Qian
  School of Information and Electronic Engineering, Zhejiang University of Science & Technology, Hangzhou 310023, China
Expert Systems with Applications: An International Journal, Volume 243, Issue C•Jun 2024 • https://doi.org/10.1016/j.eswa.2023.122753
Abstract
Estimating crowd density is a demanding task that has garnered significant research attention in urban planning, intelligent transportation, and other related fields. This study utilizes RGB and thermal images to leverage multimodal information ...
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MC³Net: Multimodality Cross-Guided Compensation Coordination Network for RGB-T Crowd Counting
- Wujie Zhou
  School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou, China
  ,
- Xun Yang
  School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou, China
  ,
- Jingsheng Lei
  School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou, China
  ,
- Weiqing Yan
  School of Computer Science and Engineering, Nanyang Technological University, Jurong West, Singapore
  ,
- Lu Yu
  Institute of Information and Communication Engineering, Zhejiang University, Hangzhou, China
IEEE Transactions on Intelligent Transportation Systems, Volume 25, Issue 5•May 2024, pp 4156-4165 • https://doi.org/10.1109/TITS.2023.3321328
Owing to the expansion in processing of industrial information through advances in machine learning, the demand for accurate crowd counting in various applications is increasing. We propose a multimodality cross-guided compensation coordination network (...
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Modal Evaluation Network via Knowledge Distillation for No-Service Rail Surface Defect Detection
- Wujie Zhou
  School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou, China
  ,
- Jiankang Hong
  School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou, China
  ,
- Weiqing Yan
  School of Computer Science and Engineering, Nanyang Technological University, Jurong West, Singapore
  ,
- Qiuping Jiang
  School of Information Science and Engineering, Ningbo University, Ningbo, China
IEEE Transactions on Circuits and Systems for Video Technology, Volume 34, Issue 5•May 2024, pp 3930-3942 • https://doi.org/10.1109/TCSVT.2023.3325229
Deep learning techniques have largely solved the problem of rail surface defect detection (SDD), however, two aspects have yet to be addressed. In most existing approaches, two red–green–blue and depth (RGB-D) streams are indiscriminately ...
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Dual-Constraint Coarse-to-Fine Network for Camouflaged Object Detection
- Guanghui Yue
  School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China
  ,
- Houlu Xiao
  School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China
  ,
- Hai Xie
  School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China
  ,
- Tianwei Zhou
  College of Management, Shenzhen University, Shenzhen, China
  ,
- Wei Zhou
  School of Computer Science and Informatics, Cardiff University, Cardiff, U.K
  ,
- Weiqing Yan
  School of Computer and Control Engineering, Yantai University, Yantai, China
  ,
- Baoquan Zhao
  School of Artificial Intelligence, Sun Yat-sen University, Zhuhai, China
  ,
- Tianfu Wang
  School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China
  ,
- Qiuping Jiang
  Faculty of Information Science and Engineering, Ningbo University, Ningbo, China
IEEE Transactions on Circuits and Systems for Video Technology, Volume 34, Issue 5•May 2024, pp 3286-3298 • https://doi.org/10.1109/TCSVT.2023.3318672
Camouflaged object detection (COD) is an important yet challenging task, with great application values in industrial defect detection, medical care, etc. The challenges mainly come from the high intrinsic similarities between target objects and ...
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HFENet: Hybrid feature encoder network for detecting salient objects in RGB-thermal images
- Fan Sun
  School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou 310023, PR China
  ,
- Wujie Zhou
  School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou 310023, PR China
  School of Computer Science and Engineering, Nanyang Technological University, Singapore 308232, Singapore
  ,
- Weiqing Yan
  School of Computer Science and Engineering, Nanyang Technological University, Singapore 308232, Singapore
  School of Computer and Control Engineering, Yantai University, Yantai 264005, China
  ,
- Yulai Zhang
  School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou 310023, PR China
Digital Signal Processing, Volume 148, Issue C•May 2024 • https://doi.org/10.1016/j.dsp.2024.104439
Abstract
Deep convolutional neural networks (CNNs) have gained prominence in computer vision applications, including RGB salient object detection (SOD), owing to the advancements in deep learning. Nevertheless, the majority of deep CNNs employ either ...
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Adaptive multi-channel Bayesian Graph Neural Network
- Dong Yang
  Department of Computer Science, Georgia State University, Atlanta, GA 30303, USA
  ,
- Zhaowei Liu
  School of Computer and Control Engineering, Yantai University, Yantai 264005, China
  ,
- Yingjie Wang
  School of Computer and Control Engineering, Yantai University, Yantai 264005, China
  ,
- Jindong Xu
  School of Computer and Control Engineering, Yantai University, Yantai 264005, China
  ,
- Weiqing Yan
  School of Computer and Control Engineering, Yantai University, Yantai 264005, China
  ,
- Ranran Li
  School of Computer and Control Engineering, Yantai University, Yantai 264005, China
  Institute Network Technology of Yantai, Yantai 264006, China
Neurocomputing, Volume 575, Issue C•Mar 2024 • https://doi.org/10.1016/j.neucom.2024.127260
Abstract
Recent years have seen a surge in interest in graph neural networks (GNNs) due to their superior performance in a range of graph and network mining applications. Graph embedding attempts to convert nodes in graph data to a low-dimensional vector ...
Highlights

Explore graph structure learning, advocate GNN’s concurrent learning from original and estimated graphs.
Adaptive integration enhances GNN’s classification using useful information from both graphs.
Introduce Bayesian inference for ...
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Progressive Adjacent-Layer coordination symmetric cascade network for semantic segmentation of Multimodal remote sensing images
- Xiaomin Fan
  School of Information & Electronic Engineering, Zhejiang University of Science & Technology, Hangzhou 310023, China
  ,
- Wujie Zhou
  School of Information & Electronic Engineering, Zhejiang University of Science & Technology, Hangzhou 310023, China
  School of Computer Science and Engineering, Nanyang Technological University, Singapore 308232, Singapore
  ,
- Xiaohong Qian
  School of Information & Electronic Engineering, Zhejiang University of Science & Technology, Hangzhou 310023, China
  ,
- Weiqing Yan
  School of Computer Science and Engineering, Nanyang Technological University, Singapore 308232, Singapore
  School of Computer and Control Engineering, Yantai University, Yantai 264005, China
Expert Systems with Applications: An International Journal, Volume 238, Issue PD•Mar 2024 • https://doi.org/10.1016/j.eswa.2023.121999
Abstract
Semantic segmentation of remote sensing images is a fundamental task in computer vision, with significant applications in forest and farmland cover surveys, geological disaster monitoring, and other related fields. The inclusion of digital ...
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Boundary uncertainty aware network for automated polyp segmentation
- Guanghui Yue
  National-Reginoal Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Marshall Laboratory of Biomedical Engineering, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen 518060, China
  ,
- Guibin Zhuo
  National-Reginoal Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Marshall Laboratory of Biomedical Engineering, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen 518060, China
  ,
- Weiqing Yan
  School of Computer and Control Engineering, Yantai University, Yantai 264005, China
  ,
- Tianwei Zhou
  College of Management, Shenzhen University, Shenzhen 518060, China
  ,
- Chang Tang
  School of Computer Science, China University of Geosciences, Wuhan 430074, China
  ,
- Peng Yang
  National-Reginoal Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Marshall Laboratory of Biomedical Engineering, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen 518060, China
  ,
- Tianfu Wang
  National-Reginoal Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Marshall Laboratory of Biomedical Engineering, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen 518060, China
Neural Networks, Volume 170, Issue C•Feb 2024, pp 390-404 • https://doi.org/10.1016/j.neunet.2023.11.050
Abstract
Recently, leveraging deep neural networks for automated colorectal polyp segmentation has emerged as a hot topic due to the favored advantages in evading the limitations of visual inspection, e.g., overwork and subjectivity. However, most ...
Highlights

A boundary uncertainty aware network is proposed for accurate polyp segmentation.
A boundary exploration module is proposed to explore boundary cues of polyps.
A boundary uncertainty aware module is proposed to seek error-prone ...
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Perceptual Quality Assessment of Retouched Face Images
- Guanghui Yue
  National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen, China
  ,
- Honglv Wu
  National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen, China
  ,
- Qiuping Jiang
  School of Information Science and Engineering, Ningbo University, Ningbo, China
  ,
- Tianwei Zhou
  College of Management, Shenzhen University, Shenzhen, China
  ,
- Weiqing Yan
  School of Computer and Control Engineering, Yantai University, Yantai, China
  ,
- Tianfu Wang
  National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen, China
IEEE Transactions on Multimedia, Volume 26•2024, pp 5741-5752 • https://doi.org/10.1109/TMM.2023.3338412
Nowadays, it is a common practice to retouch face images before sharing them on websites, social media, and even identification cards. In response, increased criticisms have appeared about taking photo retouching to an extreme. This naturally leads to the ...
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UTLNet: Uncertainty-Aware Transformer Localization Network for RGB-Depth Mirror Segmentation
- Wujie Zhou
  School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou, China
  ,
- Yuqi Cai
  School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou, China
  ,
- Liting Zhang
  School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou, China
  ,
- Weiqing Yan
  School of Computer Science and Engineering, Nanyang Technological University, Singapore
  ,
- Lu Yu
  Institute of Information and Communication Engineering, Zhejiang University, Hangzhou, China
IEEE Transactions on Multimedia, Volume 26•2024, pp 4564-4574 • https://doi.org/10.1109/TMM.2023.3323890
Mirror segmentation, an emerging discipline in the field of computer vision, involves the identification and marking of mirrors in an image. Current mirror segmentation methods rely on fixed mirror elements as features for object segmentation. However, ...
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EGFNet: Edge-Aware Guidance Fusion Network for RGB–Thermal Urban Scene Parsing
- Shaohua Dong
  School of Information & Electronic Engineering, Zhejiang University of Science & Technology, Hangzhou, China
  ,
- Wujie Zhou
  School of Information & Electronic Engineering, Zhejiang University of Science & Technology, Hangzhou, China
  ,
- Caie Xu
  School of Information & Electronic Engineering, Zhejiang University of Science & Technology, Hangzhou, China
  ,
- Weiqing Yan
  School of Computer Science and Engineering, Nanyang Technological University, Jurong West, Singapore
IEEE Transactions on Intelligent Transportation Systems, Volume 25, Issue 1•Jan. 2024, pp 657-669 • https://doi.org/10.1109/TITS.2023.3306368
Urban scene parsing is the core of the intelligent transportation system, and RGB–thermal urban scene parsing has recently attracted increasing research interest in the field of computer vision. However, most existing approaches fail to perform ...
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MMSMCNet: Modal Memory Sharing and Morphological Complementary Networks for RGB-T Urban Scene Semantic Segmentation
- Wujie Zhou
  School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou, China
  ,
- Han Zhang
  School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou, China
  ,
- Weiqing Yan
  School of Computer and Control Engineering, Yantai University, Yantai, China
  ,
- Weisi Lin
  School of Computer Science and Engineering, Nanyang Technological University, Jurong West, Singapore
IEEE Transactions on Circuits and Systems for Video Technology, Volume 33, Issue 12•Dec. 2023, pp 7096-7108 • https://doi.org/10.1109/TCSVT.2023.3275314
Combining color (RGB) images with thermal images can facilitate semantic segmentation of poorly lit urban scenes. However, for RGB-thermal (RGB-T) semantic segmentation, most existing models address cross-modal feature fusion by focusing only on exploring ...
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Collaborative structure and feature learning for multi-view clustering
- Weiqing Yan
  School of Computer and Control Engineering, Yantai University, Yantai, 264005, China
  School of Computer Science and Engineering, Nanyang Technological University, Singapore, 639798, Singapore
  ,
- Meiqi Gu
  School of Computer and Control Engineering, Yantai University, Yantai, 264005, China
  ,
- Jinlai Ren
  School of Civil Engineering, Yantai University, Yantai, 264005, China
  ,
- Guanghui Yue
  School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, 518060, China
  ,
- Zhaowei Liu
  School of Computer and Control Engineering, Yantai University, Yantai, 264005, China
  ,
- Jindong Xu
  School of Computer and Control Engineering, Yantai University, Yantai, 264005, China
  ,
- Weisi Lin
  School of Computer Science and Engineering, Nanyang Technological University, Singapore, 639798, Singapore
Information Fusion, Volume 98, Issue C•Oct 2023 • https://doi.org/10.1016/j.inffus.2023.101832
Abstract
Multi-view clustering divides similar objects into the same class through using the fused multiview information. Most multi-view clustering methods obtain clustering result by only analyzing structure relationship among samples, ignoring the ...
Highlights

Propose a Collaborative Structure and Feature Learning for multi-view clustering.
Propose a feature learning method with data pseudo-labels.
Propose structure learning with weighted tensor term for multiple subspace fusion.
The ...
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Graph-filtering and high-order bipartite graph based multiview graph clustering
- Xinying Zhao
  School of Computer and Control Engineering, Yantai University, Yantai 261400, China
  ,
- Weiqing Yan
  School of Computer and Control Engineering, Yantai University, Yantai 261400, China
  ,
- Jinlai Ren
  School of Civil Engineering, Yantai University, Yantai 261400, China
  ,
- Jindong Xu
  School of Computer and Control Engineering, Yantai University, Yantai 261400, China
  ,
- Zhaowei Liu
  School of Computer and Control Engineering, Yantai University, Yantai 261400, China
  ,
- Guanghui Yue
  School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen 518060, China
  ,
- Chang Tang
  School of Computer Science, China University of Geosciences, Wuhan 430074, China
Digital Signal Processing, Volume 133, Issue C•Mar 2023 • https://doi.org/10.1016/j.dsp.2022.103847
Abstract
Multiview clustering, which partitions data into different groups, has attracted wide attention. With increasing data, bipartite graph-based multiview clustering has become an important topic since it can achieve efficient clustering by ...
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Published By ACM
Published By ACM
Efficient Multiple Kernel Clustering via Spectral Perturbation
- Chang Tang
  China University of Geosciences & Nanjing University, Wuhan, China
  ,
- Zhenglai Li
  China University of Geosciences & Nanjing University, Wuhan, China
  ,
- Weiqing Yan
  Yantai University, Yantai, China
  ,
- Guanghui Yue
  Shenzhen University, Shenzhen, China
  ,
- Wei Zhang
  Shandong Provincial Key Laboratory of Computer Networks, Shandong Computer Science Center (National Supercomputing Center in Jinan) & Qilu University of Technology (Shandong Academy of Sciences), Jinan, China
MM '22: Proceedings of the 30th ACM International Conference on Multimedia•October 2022, pp 1603-1611• https://doi.org/10.1145/3503161.3548153

Clustering is a fundamental task in the machine learning and data mining community. Among existing clustering methods, multiple kernel clustering (MKC) has been widely investigated due to its effectiveness to capture non-linear relationships among ...
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Published By ACM
Published By ACM
Bipartite Graph-based Discriminative Feature Learning for Multi-View Clustering
- Weiqing Yan
  Yantai University, Yantai, China
  ,
- Jindong Xu
  Yantai University, Yantai, China
  ,
- Jinglei Liu
  Yantai University, Yantai, China
  ,
- Guanghui Yue
  Shenzhen University, Shenzhen, China
  ,
- Chang Tang
  China University of Geosciences, Wuhan, Wuhan, China
MM '22: Proceedings of the 30th ACM International Conference on Multimedia•October 2022, pp 3403-3411• https://doi.org/10.1145/3503161.3548144

Multi-view clustering is an important technique in machine learning research. Existing methods have improved in clustering performance, most of them learn graph structure depending on all samples, which are high complexity. Bipartite graph-based multi-...
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research-article
Stereo VoVNet-CNN for 3D object detection
- Kaiqi Su
  School of Computer and Control Engineering, Yantai University, 264005, Yantai, China
  ,
- Weiqing Yan
  School of Computer and Control Engineering, Yantai University, 264005, Yantai, China
  ,
- Xin Wei
  School of Computer and Control Engineering, Yantai University, 264005, Yantai, China
  ,
- Meiqi Gu
  School of Computer and Control Engineering, Yantai University, 264005, Yantai, China
Multimedia Tools and Applications, Volume 81, Issue 25•Oct 2022, pp 35803-35813 • https://doi.org/10.1007/s11042-021-11506-7
Abstract
3D object detection is a key issue and research in autonomous vehicle and computer vision. 3D detection methods based on stereoscopic images estimate 3D boxes and regress the object pose by exploiting the sparse and dense, semantic and geometry ...
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Shape-optimizing mesh warping method for stereoscopic panorama stitching
- Weiqing Yan
  School of Computer and Control Engineering, Yantai University, Yantai 264005, PR China
  ,
- Guanghui Yue
  School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen 518060, PR China
  ,
- Jindong Xu
  School of Computer and Control Engineering, Yantai University, Yantai 264005, PR China
  ,
- Yanwei Yu
  School of Computer and Control Engineering, Yantai University, Yantai 264005, PR China
  ,
- Kai Wang
  School of Computer and Control Engineering, Yantai University, Yantai 264005, PR China
  ,
- Chang Tang
  School of Computer Science, China University of Geosciences, Wuhan 430074, PR China
  ,
- Xiangrong Tong
  School of Computer and Control Engineering, Yantai University, Yantai 264005, PR China
Information Sciences: an International Journal, Volume 511, Issue C•Feb 2020, pp 58-73 • https://doi.org/10.1016/j.ins.2019.09.051
Abstract
In this paper, we propose a novel shape-optimizing mesh warping method for stereoscopic panorama stitching, which aims to resolve shape distortion and unnatural rotation of traditional stitching methods, simultaneously coping with the challenges, ...
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Diversity and consistency learning guided spectral embedding for multi-view clustering
- Zhenglai Li
  School of Computer Science, China University of Geosciences, Wuhan 430074, PR China
  ,
- Chang Tang
  School of Computer Science, China University of Geosciences, Wuhan 430074, PR China
  ,
- Jiajia Chen
  Department of Pharmacy, The Affiliated Huai’an Hospital of Xuzhou Medical University, Huai’an 223002, PR China
  ,
- Cheng Wan
  School of Computer Science, China University of Geosciences, Wuhan 430074, PR China
  ,
- Weiqing Yan
  School of Computer and Control Engineering, Yantai University, Yantai 264005, PR China
  ,
- Xinwang Liu
  College of Computer, National University of Defense Technology, Changsha 410073, PR China
Neurocomputing, Volume 370, Issue C•Dec 2019, pp 128-139 • https://doi.org/10.1016/j.neucom.2019.08.002
Abstract
Multi-view clustering aims to group data points into their classes. Exploiting the complementary information underlying multiple views to benefit the clustering performance is one of the topics of multi-view clustering. Most of ...
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Bibliometrics

The ACM DL is a comprehensive repository of publications from the entire field of computing.

It is ACM's intention to make the derivation of any publication statistics it generates clear to the user.

Average citations per article = The total Citation Count divided by the total Publication Count.
Citation Count = cumulative total number of times all authored works by this author were cited by other works within ACM's bibliographic database. Almost all reference lists in articles published by ACM have been captured. References lists from other publishers are less well-represented in the database. Unresolved references are not included in the Citation Count. The Citation Count is citations TO any type of work, but the references counted are only FROM journal and proceedings articles. Reference lists from books, dissertations, and technical reports have not generally been captured in the database. (Citation Counts for individual works are displayed with the individual record listed on the Author Page.)
Publication Count = all works of any genre within the universe of ACM's bibliographic database of computing literature of which this person was an author. Works where the person has role as editor, advisor, chair, etc. are listed on the page but are not part of the Publication Count.
Publication Years = the span from the earliest year of publication on a work by this author to the most recent year of publication of a work by this author captured within the ACM bibliographic database of computing literature (The ACM Guide to Computing Literature, also known as "the Guide".
Available for download = the total number of works by this author whose full texts may be downloaded from an ACM full-text article server. Downloads from external full-text sources linked to from within the ACM bibliographic space are not counted as 'available for download'.
Average downloads per article = The total number of cumulative downloads divided by the number of articles (including multimedia objects) available for download from ACM's servers.
Downloads (cumulative) = The cumulative number of times all works by this author have been downloaded from an ACM full-text article server since the downloads were first counted in May 2003. The counts displayed are updated monthly and are therefore 0-31 days behind the current date. Robotic activity is scrubbed from the download statistics.
Downloads (12 months) = The cumulative number of times all works by this author have been downloaded from an ACM full-text article server over the last 12-month period for which statistics are available. The counts displayed are usually 1-2 weeks behind the current date. (12-month download counts for individual works are displayed with the individual record.)
Downloads (6 weeks) = The cumulative number of times all works by this author have been downloaded from an ACM full-text article server over the last 6-week period for which statistics are available. The counts displayed are usually 1-2 weeks behind the current date. (6-week download counts for individual works are displayed with the individual record.)

ACM Author-Izer Service

Summary Description

ACM Author-Izer is a unique service that enables ACM authors to generate and post links on both their homepage and institutional repository for visitors to download the definitive version of their articles from the ACM Digital Library at no charge.

Downloads from these sites are captured in official ACM statistics, improving the accuracy of usage and impact measurements. Consistently linking to definitive version of ACM articles should reduce user confusion over article versioning.

ACM Author-Izer also extends ACM’s reputation as an innovative “Green Path” publisher, making ACM one of the first publishers of scholarly works to offer this model to its authors.

To access ACM Author-Izer, authors need to establish a free ACM web account. Should authors change institutions or sites, they can utilize the new ACM service to disable old links and re-authorize new links for free downloads from a different site.

How ACM Author-Izer Works

Authors may post ACM Author-Izer links in their own bibliographies maintained on their website and their own institution’s repository. The links take visitors to your page directly to the definitive version of individual articles inside the ACM Digital Library to download these articles for free.

The Service can be applied to all the articles you have ever published with ACM.

Depending on your previous activities within the ACM DL, you may need to take up to three steps to use ACM Author-Izer.

For authors who do not have a free ACM Web Account:

Go to the ACM DL http://dl.acm.org/ and click SIGN UP. Once your account is established, proceed to next step.

For authors who have an ACM web account, but have not edited their ACM Author Profile page:

Sign in to your ACM web account and go to your Author Profile page. Click "Add personal information" and add photograph, homepage address, etc. Click ADD AUTHOR INFORMATION to submit change. Once you receive email notification that your changes were accepted, you may utilize ACM Author-izer.

For authors who have an account and have already edited their Profile Page:

Sign in to your ACM web account, go to your Author Profile page in the Digital Library, look for the ACM Author-izer link below each ACM published article, and begin the authorization process. If you have published many ACM articles, you may find a batch Authorization process useful. It is labeled: "Export as: ACM Author-Izer Service"

ACM Author-Izer also provides code snippets for authors to display download and citation statistics for each “authorized” article on their personal pages. Downloads from these pages are captured in official ACM statistics, improving the accuracy of usage and impact measurements. Consistently linking to the definitive version of ACM articles should reduce user confusion over article versioning.

Note: You still retain the right to post your author-prepared preprint versions on your home pages and in your institutional repositories with DOI pointers to the definitive version permanently maintained in the ACM Digital Library. But any download of your preprint versions will not be counted in ACM usage statistics. If you use these AUTHOR-IZER links instead, usage by visitors to your page will be recorded in the ACM Digital Library and displayed on your page.

FAQ

Q. What is ACM Author-Izer?
A. ACM Author-Izer is a unique, link-based, self-archiving service that enables ACM authors to generate and post links on either their home page or institutional repository for visitors to download the definitive version of their articles for free.
Q. What articles are eligible for ACM Author-Izer?
A. ACM Author-Izer can be applied to all the articles authors have ever published with ACM. It is also available to authors who will have articles published in ACM publications in the future.

Q. Are there any restrictions on authors to use this service?
A. No. An author does not need to subscribe to the ACM Digital Library nor even be a member of ACM.

Q. What are the requirements to use this service?
A. To access ACM Author-Izer, authors need to have a free ACM web account, must have an ACM Author Profile page in the Digital Library, and must take ownership of their Author Profile page.

Q. What is an ACM Author Profile Page?
A. The Author Profile Page initially collects all the professional information known about authors from the publications record as known by the ACM Digital Library. The Author Profile Page supplies a quick snapshot of an author's contribution to the field and some rudimentary measures of influence upon it. Over time, the contents of the Author Profile page may expand at the direction of the community. Please visit the ACM Author Profile documentation page for more background information on these pages.

Q. How do I find my Author Profile page and take ownership?
A. You will need to take the following steps:
- Create a free ACM Web Account
- Sign-In to the ACM Digital Library
- Find your Author Profile Page by searching the ACM Digital Library for your name
- Find the result you authored (where your author name is a clickable link)
- Click on your name to go to the Author Profile Page
- Click the "Add Personal Information" link on the Author Profile Page
- Wait for ACM review and approval; generally less than 24 hours

Q. Why does my photo not appear?
A. Make sure that the image you submit is in .jpg or .gif format and that the file name does not contain special characters

Q. What if I cannot find the Add Personal Information function on my author page?
A. The ACM account linked to your profile page is different than the one you are logged into. Please logout and login to the account associated with your Author Profile Page.

Q. What happens if an author changes the location of his bibliography or moves to a new institution?
A. Should authors change institutions or sites, they can utilize ACM Author-Izer to disable old links and re-authorize new links for free downloads from a new location.

Q. What happens if an author provides a URL that redirects to the author’s personal bibliography page?
A. The service will not provide a free download from the ACM Digital Library. Instead the person who uses that link will simply go to the Citation Page for that article in the ACM Digital Library where the article may be accessed under the usual subscription rules.

However, if the author provides the target page URL, any link that redirects to that target page will enable a free download from the Service.

Q. What happens if the author’s bibliography lives on a page with several aliases?
A. Only one alias will work, whichever one is registered as the page containing the author’s bibliography. ACM has no technical solution to this problem at this time.

Q. Why should authors use ACM Author-Izer?
A. ACM Author-Izer lets visitors to authors’ personal home pages download articles for no charge from the ACM Digital Library. It allows authors to dynamically display real-time download and citation statistics for each “authorized” article on their personal site.

Q. Does ACM Author-Izer provide benefits for authors?
A. Downloads of definitive articles via Author-Izer links on the authors’ personal web page are captured in official ACM statistics to more accurately reflect usage and impact measurements.

Authors who do not use ACM Author-Izer links will not have downloads from their local, personal bibliographies counted. They do, however, retain the existing right to post author-prepared preprint versions on their home pages or institutional repositories with DOI pointers to the definitive version permanently maintained in the ACM Digital Library.

Q. How does ACM Author-Izer benefit the computing community?
A. ACM Author-Izer expands the visibility and dissemination of the definitive version of ACM articles. It is based on ACM’s strong belief that the computing community should have the widest possible access to the definitive versions of scholarly literature. By linking authors’ personal bibliography with the ACM Digital Library, user confusion over article versioning should be reduced over time.

In making ACM Author-Izer a free service to both authors and visitors to their websites, ACM is emphasizing its continuing commitment to the interests of its authors and to the computing community in ways that are consistent with its existing subscription-based access model.

Q. How do authors access ACM Author-Izer?
A. See How to Use

Q. Why can’t I find my most recent publication in my ACM Author Profile Page?
A. There is a time delay between publication and the process which associates that publication with an Author Profile Page. Right now, that process usually takes 4-8 weeks.

Q. How does ACM Author-Izer expand ACM’s “Green Path” Access Policies?
A. ACM Author-Izer extends the rights and permissions that authors retain even after copyright transfer to ACM, which has been among the “greenest” publishers. ACM enables its author community to retain a wide range of rights related to copyright and reuse of materials. They include:
- Posting rights that ensure free access to their work outside the ACM Digital Library and print publications
- Rights to reuse any portion of their work in new works that they may create
- Copyright to artistic images in ACM’s graphics-oriented publications that authors may want to exploit in commercial contexts
- All patent rights, which remain with the original owner

Weiqing Yan

Weiqing Yan

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Results

DSANet-KD: Dual Semantic Approximation Network via Knowledge Distillation for Rail Surface Defect Detection

CAGNet: Coordinated attention guidance network for RGB-T crowd counting

MC³Net: Multimodality Cross-Guided Compensation Coordination Network for RGB-T Crowd Counting

Modal Evaluation Network via Knowledge Distillation for No-Service Rail Surface Defect Detection

Dual-Constraint Coarse-to-Fine Network for Camouflaged Object Detection

HFENet: Hybrid feature encoder network for detecting salient objects in RGB-thermal images

Adaptive multi-channel Bayesian Graph Neural Network

Progressive Adjacent-Layer coordination symmetric cascade network for semantic segmentation of Multimodal remote sensing images

Boundary uncertainty aware network for automated polyp segmentation

Perceptual Quality Assessment of Retouched Face Images

UTLNet: Uncertainty-Aware Transformer Localization Network for RGB-Depth Mirror Segmentation

EGFNet: Edge-Aware Guidance Fusion Network for RGB–Thermal Urban Scene Parsing

MMSMCNet: Modal Memory Sharing and Morphological Complementary Networks for RGB-T Urban Scene Semantic Segmentation

Collaborative structure and feature learning for multi-view clustering

Graph-filtering and high-order bipartite graph based multiview graph clustering

Efficient Multiple Kernel Clustering via Spectral Perturbation

Bipartite Graph-based Discriminative Feature Learning for Multi-View Clustering

Stereo VoVNet-CNN for 3D object detection

Shape-optimizing mesh warping method for stereoscopic panorama stitching

Diversity and consistency learning guided spectral embedding for multi-view clustering