Zailiang Chen
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- Neurocomputing (3)
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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)
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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
AbstractOptical 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 ...
- 0Citation
MetricsTotal Citations0
- Hailan Shen
- Article
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_5AbstractPlacenta 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 ...
- 0Citation
MetricsTotal Citations0
- Zailiang Chen
- research-article
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.2022.3179608It 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 ...
- 1Citation
MetricsTotal Citations1
- Ping Jiang
- research-article
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.2023.106908AbstractAccurate 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 ...
- 0Citation
MetricsTotal Citations0
- Zailiang Chen
- Article
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_1AbstractThe 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 ...
- 0Citation
MetricsTotal Citations0
- Yajing Li
- 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.2022.08.004AbstractPrevious 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, ...
- 0Citation
MetricsTotal Citations0
- Zailiang Chen
- Article
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
AbstractMost 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 ...
- 0Citation
MetricsTotal Citations0
- Zailiang Chen
- Article
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
AbstractToday’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 ...
- 0Citation
MetricsTotal Citations0
- Rongchang Zhao
- Article
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_93AbstractBrain 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,...
- 2Citation
MetricsTotal Citations2
- Hao Wei
- Article
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_3AbstractAccurate 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 (...
- 1Citation
MetricsTotal Citations1
- Rongchang Zhao
- research-article
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.2019.05.039AbstractWhen 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 ...
- 10Citation
MetricsTotal Citations10
- Qing Liu
- article
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/s10916-019-1303-8Glaucoma 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 ...
- 4Citation
MetricsTotal Citations4
- Zailiang Chen
- research-articlefree
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.v33i01.3301809Evidence 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 ...
- 2Citation
- 29
- Downloads
MetricsTotal Citations2Total Downloads29Last 12 Months20Last 6 weeks4
- Rongchang Zhao
- research-article
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.2017.2703081Most 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 ...
- 8Citation
MetricsTotal Citations8
- Qing Liu
- research-article
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.2016.07.016In 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) ...
- 4Citation
MetricsTotal Citations4
- Hui Wu
- article
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.2016.075392With 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, ...
- 0Citation
MetricsTotal Citations0
- Zailiang Chen
- article
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-yEfficient 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 ...
- 1Citation
MetricsTotal Citations1
- Beiji Zou
- research-article
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.2015.09.017A 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 ...
- 2Citation
MetricsTotal Citations2
- Beiji Zou
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- 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. 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