Zailiang Chen

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Zailiang Chen (18)
Beiji Zou (8)
Hailan Shen (8)
Rongchang Zhao (7)
Qing Liu (5)
Xianxian Zheng (3)
Chengzhang Zhu (2)
Guoying Zhao (2)
Shuo Li (2)
Xiaopeng Hong (2)
Ziyang Zeng (2)
Feng Shi (1)
Hongpu Fu (1)
Shichao Zhang (1)
Xiang Sean Zhou (1)
Xiaoheng Deng (1)
Xiaoyun Zhang (1)
Xiyao Liu (1)
Yuqian Zhao (1)
Zhong Xue (1)

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Neurocomputing (3)
Computers in Biology and Medicine (1)
IEEE Transactions on Image Processing (1)
IEEE Transactions on Knowledge and Data Engineering (1)
International Journal of Autonomous and Adaptive Communications Systems (1)
Journal of Medical Systems (1)
Journal of Visual Communication and Image Representation (1)
Multimedia Systems (1)
Pattern Recognition (1)

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AAAI'19/IAAI'19/EAAI'19: Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence and Thirty-First Innovative Applications of Artificial Intelligence Conference and Ninth AAAI Symposium on Educational Advances in Artificial Intelligence (1)
Computer Vision – ECCV 2020 (1)
Computer Vision – ECCV 2020 (1)
Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 (1)
Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 (1)
Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 (1)
Pattern Recognition and Computer Vision (1)

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Springer-Verlag (7)
Elsevier Science Publishers B. V. (3)
AAAI Press (1)
Academic Press, Inc. (1)
Elsevier Science Inc. (1)
IEEE Educational Activities Department (1)
IEEE Press (1)
Inderscience Publishers (1)
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research-article
HAIC-NET: Semi-supervised OCTA vessel segmentation with self-supervised pretext task and dual consistency training
- Hailan Shen
  School of Computer Science and Engineering, Central South University, Changsha, 410083, China
  ,
- Zheng Tang
  School of Computer Science and Engineering, Central South University, Changsha, 410083, China
  ,
- Yajing Li
  School of Computer Science and Engineering, Central South University, Changsha, 410083, China
  ,
- Xuanchu Duan
  Changsha Aier Eye Hospital, Changsha, 410015, China
  ,
- Zailiang Chen
  School of Computer Science and Engineering, Central South University, Changsha, 410083, China
Pattern Recognition, Volume 151, Issue C•Jul 2024 • https://doi.org/10.1016/j.patcog.2024.110429
Abstract
Optical Coherence Tomography Angiography(OCTA) vessel segmentation is a challenging task. On the one hand, the complex structure of the capillary networks presents significant obstacles to achieving accurate vessel segmentation. On the other hand,...
Highlights

A novel semi-supervised network HAIC-Net for OCTA vessel segmentation.
A self-supervised pretext task to extract vascular features from unlabeled images.
A novel topological-based consistency to enhance the connectivity of ...
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Geometry-Adaptive Network for Robust Detection of Placenta Accreta Spectrum Disorders
- Zailiang Chen
  https://ror.org/00f1zfq44School of Computer Science and Engineering, Central South University, Changsha, China
  ,
- Jiang Zhu
  https://ror.org/00f1zfq44School of Computer Science and Engineering, Central South University, Changsha, China
  ,
- Hailan Shen
  https://ror.org/00f1zfq44School of Computer Science and Engineering, Central South University, Changsha, China
  ,
- Hui Liu
  Xiangya Hospital, Central South University, Changsha, China
  ,
- Yajing Li
  https://ror.org/00f1zfq44School of Computer Science and Engineering, Central South University, Changsha, China
  ,
- Rongchang Zhao
  https://ror.org/00f1zfq44School of Computer Science and Engineering, Central South University, Changsha, China
  ,
- Feiyang Yu
  https://ror.org/00f1zfq44School of Computer Science and Engineering, Central South University, Changsha, China
Medical Image Computing and Computer Assisted Intervention – MICCAI 2023•October 2023, pp 43-53• https://doi.org/10.1007/978-3-031-43990-2_5
Abstract
Placenta accreta spectrum (PAS) is a high-risk obstetric disorder associated with significant morbidity and mortality. Since the abnormal invasion usually occurs near the uteroplacental interface, there is a large geometry variation in the lesion ...
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Hypergraph Representation for Detecting 3D Objects From Noisy Point Clouds
- Ping Jiang
  School of Computer Science and Engineering, Central South University, Changsha, Hunan, China
  ,
- Xiaoheng Deng
  School of Computer Science and Engineering, Central South University, Changsha, Hunan, China
  ,
- Leilei Wang
  School of Computer Science and Engineering, Central South University, Changsha, Hunan, China
  ,
- Zailiang Chen
  School of Computer Science and Engineering, Central South University, Changsha, Hunan, China
  ,
- Shichao Zhang
  School of Computer Science and Engineering, Central South University, Changsha, Hunan, China
IEEE Transactions on Knowledge and Data Engineering, Volume 35, Issue 7•July 2023, pp 7016-7029 • https://doi.org/10.1109/TKDE.2022.3179608
It is challenging to detect 3D objects from noise point clouds by Graph Neural Networks (GNNs), though graph-based methods have shown promising results in 3D classifications. Since strong robustness against noise is offered by hypergraph, a relative ...
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FDCT: Fusion-Guided Dual-View Consistency Training for semi-supervised tissue segmentation on MRI
- Zailiang Chen
  Central South University, No. 932 Lushan South Road, Changsha, 410000, China
  ,
- Yazheng Hou
  Central South University, No. 932 Lushan South Road, Changsha, 410000, China
  ,
- Hui Liu
  Xiangya Hospital of Central South University, No. 87 Xiangya Road, 410000, China
  ,
- Ziyu Ye
  Xi’an Jiaotong-liverpool University, No. 111 Renai Road, 215000, China
  ,
- Rongchang Zhao
  Central South University, No. 932 Lushan South Road, Changsha, 410000, China
  ,
- Hailan Shen
  Central South University, No. 932 Lushan South Road, Changsha, 410000, China
Computers in Biology and Medicine, Volume 160, Issue C•Jun 2023 • https://doi.org/10.1016/j.compbiomed.2023.106908
Abstract
Accurate tissue segmentation on MRI is important for physicians to make diagnosis and treatment for patients. However, most of the models are only designed for single-task tissue segmentation, and tend to lack generality to other MRI tissue ...
Highlights

We propose a universal semi-supervised tissue segmentation framework on MRI called FDCT.
We improve the CBAM based on the task of this paper, which brings a boost to the network performance.
We propose the SBOM that generates ...
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ED-AnoNet: Elastic Distortion-Based Unsupervised Network for OCT Image Anomaly Detection
- Yajing Li
  School of Computer Science and Engineering, Central South University, 410083, Hunan, China
  ,
- Junhua Li
  School of Computer Science and Engineering, Central South University, 410083, Hunan, China
  ,
- Hailan Shen
  School of Computer Science and Engineering, Central South University, 410083, Hunan, China
  ,
- Zailiang Chen
  School of Computer Science and Engineering, Central South University, 410083, Hunan, China
Pattern Recognition and Computer Vision•October 2022, pp 3-15• https://doi.org/10.1007/978-3-031-18910-4_1
Abstract
The use of anomaly detection methods based on the deep convolutional neural network has shown its success on optical coherence tomography (OCT) images. However, these methods only train normal samples from healthy subjects, which are insensitive ...
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research-article
Marginal samples for knowledge distillation
- Zailiang Chen
  School of Computer Science and Engineering, Central South University, Hunan, Changsha 410083, China
  ,
- Xianxian Zheng
  School of Computer Science and Engineering, Central South University, Hunan, Changsha 410083, China
  ,
- Hailan Shen
  School of Computer Science and Engineering, Central South University, Hunan, Changsha 410083, China
  ,
- Jinghao Zhang
  School of Computer Science and Engineering, Central South University, Hunan, Changsha 410083, China
  ,
- Peishan Dai
  School of Computer Science and Engineering, Central South University, Hunan, Changsha 410083, China
  ,
- Rongchang Zhao
  School of Computer Science and Engineering, Central South University, Hunan, Changsha 410083, China
Neurocomputing, Volume 507, Issue C•Oct 2022, pp 157-165 • https://doi.org/10.1016/j.neucom.2022.08.004
Abstract
Previous work like Category Structure Knowledge Distillation proposes to construct category-wise relations for knowledge distillation by introducing intra-category and inter-category relations based on category centers. However, ...
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Improving Knowledge Distillation via Category Structure
- Zailiang Chen
  School of Computer Science and Engineering, Central South University, 410083, Changsha, Hunan, China
  ,
- Xianxian Zheng
  School of Computer Science and Engineering, Central South University, 410083, Changsha, Hunan, China
  ,
- Hailan Shen
  School of Computer Science and Engineering, Central South University, 410083, Changsha, Hunan, China
  ,
- Ziyang Zeng
  School of Computer Science and Engineering, Central South University, 410083, Changsha, Hunan, China
  ,
- Yukun Zhou
  Centre for Medical Image Computing, University College London, WC1V 6LJ, London, UK
  ,
- Rongchang Zhao
  School of Computer Science and Engineering, Central South University, 410083, Changsha, Hunan, China
Computer Vision – ECCV 2020•August 2020, pp 205-219• https://doi.org/10.1007/978-3-030-58604-1_13
Abstract
Most previous knowledge distillation frameworks train the student to mimic the teacher’s output of each sample or transfer cross-sample relations from the teacher to the student. Nevertheless, they neglect the structured relations at a category ...
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EGDCL: An Adaptive Curriculum Learning Framework for Unbiased Glaucoma Diagnosis
- Rongchang Zhao
  School of Computer Science, Central South University, Changsha, China
  ,
- Xuanlin Chen
  School of Computer Science, Central South University, Changsha, China
  ,
- Zailiang Chen
  School of Computer Science, Central South University, Changsha, China
  ,
- Shuo Li
  Western University, London, ON, Canada
Computer Vision – ECCV 2020•August 2020, pp 190-205• https://doi.org/10.1007/978-3-030-58589-1_12
Abstract
Today’s computer-aided diagnosis (CAD) model is still far from the clinical practice of glaucoma detection, mainly due to the training bias originating from 1) the normal-abnormal class imbalance and 2) the rare but significant hard samples in ...
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Regression-Based Line Detection Network for Delineation of Largely Deformed Brain Midline
- Hao Wei
  Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China
  School of Computer Science and Engineering, Central South University, Changsha, Hunan, China
  ,
- Xiangyu Tang
  Department of Radiology, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China
  ,
- Minqing Zhang
  Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China
  College of Software Engineering, Southeast University, Jiangsu, China
  ,
- Qingfeng Li
  Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China
  School of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, China
  ,
- Xiaodan Xing
  Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China
  Medical Imaging Center, Shanghai Advanced Research Institute, Shanghai, China
  ,
- Xiang Sean Zhou
  Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China
  ,
- Zhong Xue
  Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China
  ,
- Wenzhen Zhu
  Department of Radiology, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China
  ,
- Zailiang Chen
  School of Computer Science and Engineering, Central South University, Changsha, Hunan, China
  ,
- Feng Shi
  Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China
Medical Image Computing and Computer Assisted Intervention – MICCAI 2019•October 2019, pp 839-847• https://doi.org/10.1007/978-3-030-32248-9_93
Abstract
Brain midline shift is often caused by various clinical conditions such as high intracranial pressure, which can be deadly. To facilitate clinical evaluation, automated methods have been proposed to classify whether midline shift is severe or not,...
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Multi-index Optic Disc Quantification via MultiTask Ensemble Learning
- Rongchang Zhao
  School of Computer Science and Engineering, Central South University, Changsha, China
  Hunan Engineering Research Center of Machine Vision and Intelligent Medicine, Changsha, China
  ,
- Zailiang Chen
  School of Computer Science and Engineering, Central South University, Changsha, China
  Hunan Engineering Research Center of Machine Vision and Intelligent Medicine, Changsha, China
  ,
- Xiyao Liu
  School of Computer Science and Engineering, Central South University, Changsha, China
  Hunan Engineering Research Center of Machine Vision and Intelligent Medicine, Changsha, China
  ,
- Beiji Zou
  School of Computer Science and Engineering, Central South University, Changsha, China
  Hunan Engineering Research Center of Machine Vision and Intelligent Medicine, Changsha, China
  ,
- Shuo Li
  Department of Medical Imaging and Medical Biophysics, Western University, London, Canada
  Digital Imaging Group of London, London, ON, Canada
Medical Image Computing and Computer Assisted Intervention – MICCAI 2019•October 2019, pp 21-29• https://doi.org/10.1007/978-3-030-32239-7_3
Abstract
Accurate quantification of optic disc (OD) is clinically significant for the assessment and diagnosis of ophthalmic disease. Multi-index OD quantification, i.e., to simultaneously quantify a set of clinical indices including 2 vertical diameters (...
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A spatial-aware joint optic disc and cup segmentation method
- Qing Liu
  School of Computer Science and Engineering, Central South University, China
  ,
- Xiaopeng Hong
  Xian Jiaotong University, China
  Centre for Machine Vision and Signal Analysis, University of Oulu, Finland
  ,
- Shuo Li
  Department of Medical Imaging, Western University, Canada
  ,
- Zailiang Chen
  School of Computer Science and Engineering, Central South University, China
  ,
- Guoying Zhao
  Centre for Machine Vision and Signal Analysis, University of Oulu, Finland
  ,
- Beiji Zou
  School of Computer Science and Engineering, Central South University, China
  Hunan Province Engineering Technology Research Center of Computer Vision and Intelligent Medical Treatment, China
Neurocomputing, Volume 359, Issue C•Sep 2019, pp 285-297 • https://doi.org/10.1016/j.neucom.2019.05.039
Abstract
When dealing with the optic disc and cup in the optical nerve head images, their joint segmentation confronts two critical problems. One is that the spatial layout of the vessels in the optic nerve head images is variant. The other is ...
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Combination of Enhanced Depth Imaging Optical Coherence Tomography and Fundus Images for Glaucoma Screening
- Zailiang Chen
  School of Computer Science and Engineering, Central South University, Changsha, China 410083
  ,
- Xianxian Zheng
  School of Computer Science and Engineering, Central South University, Changsha, China 410083
  ,
- Hailan Shen
  School of Computer Science and Engineering, Central South University, Changsha, China 410083
  ,
- Ziyang Zeng
  School of Computer Science and Engineering, Central South University, Changsha, China 410083
  ,
- Qing Liu
  School of Computer Science and Engineering, Central South University, Changsha, China 410083
  ,
- Zhuo Li
  The Second Xiangya Hospital of Central South University, Changsha, China 410011
Journal of Medical Systems, Volume 43, Issue 6•Jun 2019, pp 1-12 • https://doi.org/10.1007/s10916-019-1303-8

Glaucoma is an eye disease that damages the optic nerve and can lead to irreversible loss of peripheral vision gradually and even blindness without treatment. Thus, diagnosing glaucoma in the early stage is essential for treatment. In this paper, an ...
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Weakly-supervised simultaneous evidence identification and segmentation for automated glaucoma diagnosis
- Rongchang Zhao
  School of Information Science and Engineering, Central South University, Changsha, China and Hunan Engineering Research Center of Machine Vision and Intelligent Medicine, Changsha, China
  ,
- Wangmin Liao
  School of Information Science and Engineering, Central South University, Changsha, China and Hunan Engineering Research Center of Machine Vision and Intelligent Medicine, Changsha, China
  ,
- Beiji Zou
  School of Information Science and Engineering, Central South University, Changsha, China and Hunan Engineering Research Center of Machine Vision and Intelligent Medicine, Changsha, China
  ,
- Zailiang Chen
  School of Information Science and Engineering, Central South University, Changsha, China and Hunan Engineering Research Center of Machine Vision and Intelligent Medicine, Changsha, China
  ,
- Shuo Li
  University of Western Ontario, London, ON, Canada
AAAI'19/IAAI'19/EAAI'19: Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence and Thirty-First Innovative Applications of Artificial Intelligence Conference and Ninth AAAI Symposium on Educational Advances in Artificial Intelligence•January 2019, Article No.: 100, pp 809-816• https://doi.org/10.1609/aaai.v33i01.3301809

Evidence Identification, optic disc segmentation and automated glaucoma diagnosis are the most clinically significant tasks for clinicians to assess fundus images. However, delivering the three tasks simultaneously is extremely challenging due to the high ...
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Hierarchical Contour Closure-Based Holistic Salient Object Detection
- Qing Liu
  School of Information Science and Engineering, Central South University, Changsha, Hunan, China
  ,
- Xiaopeng Hong
  Center for Machine Vision and Signal Analysis, University of Oulu, Oulu, Finland
  ,
- Beiji Zou
  School of Information Science and Engineering, Central South University, Changsha, Hunan, China
  ,
- Jie Chen
  Center for Machine Vision and Signal Analysis, University of Oulu, Oulu, Finland
  ,
- Zailiang Chen
  School of Information Science and Engineering, Central South University, Changsha, Hunan, China
  ,
- Guoying Zhao
  Center for Machine Vision and Signal Analysis, University of Oulu, Oulu, Finland
IEEE Transactions on Image Processing, Volume 26, Issue 9•Sept. 2017, pp 4537-4552 • https://doi.org/10.1109/TIP.2017.2703081
Most existing salient object detection methods compute the saliency for pixels, patches, or superpixels by contrast. Such fine-grained contrast-based salient object detection methods are stuck with saliency attenuation of the salient object and saliency ...
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Natural scene text detection by multi-scale adaptive color clustering and non-text filtering
- Hui Wu
  Center for Ophthalmic Imaging Research, Central South University, Changsha, Hunan 410012, China
  ,
- Beiji Zou
  Center for Ophthalmic Imaging Research, Central South University, Changsha, Hunan 410012, China
  ,
- Yu-qian Zhao
  School of Geosciences and Info-Physics, Central South University, Changsha 410083, China
  ,
- Zailiang Chen
  Center for Ophthalmic Imaging Research, Central South University, Changsha, Hunan 410012, China
  ,
- Chengzhang Zhu
  Center for Ophthalmic Imaging Research, Central South University, Changsha, Hunan 410012, China
  ,
- Jianjing Guo
  Center for Ophthalmic Imaging Research, Central South University, Changsha, Hunan 410012, China
Neurocomputing, Volume 214, Issue C•November 2016, pp 1011-1025 • https://doi.org/10.1016/j.neucom.2016.07.016

In recent years, natural scene text detection gains increasing attention because it plays an important role in many computer related techniques. In this paper, we propose a text detection method consisting of two major steps: connected components (CCs) ...
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ROI extraction based on visual salience and visual evaluation
- Zailiang Chen
  School of Information Science and Engineering, Central South University, 411 Computer Building, No. 932, South Lushan Road, Changsha City, Hunan Province, 410083, China
  ,
- Huajie Huang
  School of Information Science and Engineering, Central South University, 411 Computer Building, No. 932, South Lushan Road, Changsha City, Hunan Province, 410083, China
  ,
- Hailan Shen
  School of Information Science and Engineering, Central South University, 411 Computer Building, No. 932, South Lushan Road, Changsha City, Hunan Province, 410083, China
  ,
- Beiji Zou
  School of Information Science and Engineering, Central South University, 411 Computer Building, No. 932, South Lushan Road, Changsha City, Hunan Province, 410083, China
  ,
- Jiang Wang
  Jinchuan Group Engineering and Construction Co., Ltd., Jinchang City, Gansu Province, 737104, China
International Journal of Autonomous and Adaptive Communications Systems, Volume 9, Issue 1/2•March 2016, pp 57-70 • https://doi.org/10.1504/IJAACS.2016.075392

With saliency map generated from visual attention model, this paper proposes two regions of interest ROI extraction algorithms respectively based on salient points and saliency regions. The former one adopts statistical and clustering techniques, ...
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Saliency detection using boundary information
- Beiji Zou
  School of Information Science and Engineering Central South University, Changsha, People's Republic of China 410083
  ,
- Qing Liu
  School of Information Science and Engineering Central South University, Changsha, People's Republic of China 410083
  ,
- Zailiang Chen
  School of Information Science and Engineering Central South University, Changsha, People's Republic of China 410083
  ,
- Shijian Liu
  School of Information Science and Engineering Central South University, Changsha, People's Republic of China 410083
  ,
- Xiaoyun Zhang
  School of Information Science and Engineering Central South University, Changsha, People's Republic of China 410083
Multimedia Systems, Volume 22, Issue 2•March 2016, pp 245-253 • https://doi.org/10.1007/s00530-014-0449-y

Efficient and robust saliency detection is a fundamental problem in computer vision field for its wide applications, such as image segmentation and image retargeting, etc. In this paper, with the aim of uniformly highlighting the salient objects and ...
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Surroundedness based multiscale saliency detection
- Beiji Zou
  School of Information Science and Engineering, Central South University, Ministry of Education-China Mobile Joint Laboratory For Mobile Health, China
  ,
- Qing Liu
  School of Information Science and Engineering, Central South University, Ministry of Education-China Mobile Joint Laboratory For Mobile Health, China
  ,
- Zailiang Chen
  School of Information Science and Engineering, Central South University, Ministry of Education-China Mobile Joint Laboratory For Mobile Health, China
  ,
- Hongpu Fu
  School of Information Science and Engineering, Central South University, Ministry of Education-China Mobile Joint Laboratory For Mobile Health, China
  ,
- Chengzhang Zhu
  School of Information Science and Engineering, Central South University, Ministry of Education-China Mobile Joint Laboratory For Mobile Health, China
Journal of Visual Communication and Image Representation, Volume 33, Issue C•November 2015, pp 378-388 • https://doi.org/10.1016/j.jvcir.2015.09.017

A region based saliency detection method is proposed.A region extraction method is proposed to group similar elements into a region.Surroundedness is proposed for saliency detection.Surroundedness is measured via the average outer contour confidence of ...
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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

Zailiang Chen

Zailiang Chen

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HAIC-NET: Semi-supervised OCTA vessel segmentation with self-supervised pretext task and dual consistency training

Geometry-Adaptive Network for Robust Detection of Placenta Accreta Spectrum Disorders

Hypergraph Representation for Detecting 3D Objects From Noisy Point Clouds

FDCT: Fusion-Guided Dual-View Consistency Training for semi-supervised tissue segmentation on MRI

ED-AnoNet: Elastic Distortion-Based Unsupervised Network for OCT Image Anomaly Detection

Marginal samples for knowledge distillation

Improving Knowledge Distillation via Category Structure

EGDCL: An Adaptive Curriculum Learning Framework for Unbiased Glaucoma Diagnosis

Regression-Based Line Detection Network for Delineation of Largely Deformed Brain Midline

Multi-index Optic Disc Quantification via MultiTask Ensemble Learning

A spatial-aware joint optic disc and cup segmentation method

Combination of Enhanced Depth Imaging Optical Coherence Tomography and Fundus Images for Glaucoma Screening

Weakly-supervised simultaneous evidence identification and segmentation for automated glaucoma diagnosis

Hierarchical Contour Closure-Based Holistic Salient Object Detection

Natural scene text detection by multi-scale adaptive color clustering and non-text filtering

ROI extraction based on visual salience and visual evaluation

Saliency detection using boundary information

Surroundedness based multiscale saliency detection