Residual Connection-Based Encoder Decoder Network (RCED-Net) for Retinal Vessel Segmentation Khan, Tariq, Alhussein, M., Aurangzeb, K., Arsalan, M., Naqvi, S.S. and Nawaz, S.J. 2020, Residual Connection-Based Encoder Decoder Network (RCED-Net) for Retinal Vessel Segmentation, IEEE Access, vol. 8, pp. 131257-131272, doi: 10.1109/ACCESS.2020.3008899. Attached Files Name Description MIMEType Size Downloads Title Residual Connection-Based Encoder Decoder Network (RCED-Net) for Retinal Vessel Segmentation Author(s) Khan, Tariq orcid.org/0000-0002-7477-1591 Alhussein, M. Aurangzeb, K. Arsalan, M. Naqvi, S.S. Nawaz, S.J. Journal name IEEE Access Volume number 8 Start page 131257 End page 131272 Total pages 16 Publisher IEEE Place of publication Piscataway, N.J. Publication date 2020 ISSN 2169-3536 2169-3536 Keyword(s) Science & Technology Technology Computer Science, Information Systems Engineering, Electrical & Electronic Telecommunications Computer Science Engineering Retinal vessel segmentation convolutional neural network pixel-wise semantic segmentation skip connection low-level semantic information residual edge information BLOOD-VESSELS MATCHED-FILTER IMAGES EXTRACTION LEVEL MODEL Language eng DOI 10.1109/ACCESS.2020.3008899 Indigenous content off Field of Research 08 Information and Computing Sciences 09 Engineering 10 Technology HERDC Research category C1.1 Refereed article in a scholarly journal Free to Read? Yes Persistent URL http://hdl.handle.net/10536/DRO/DU:30144325 Document type: Journal Article Collections: Faculty of Science, Engineering and Built Environment School of Information Technology Open Access Collection Related Links Link Description Link to full-text (open access)     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au. Versions Version Filter Type Tue, 20 Oct 2020, 10:37:59 EST Wed, 21 Oct 2020, 04:00:45 EST Wed, 21 Oct 2020, 05:05:29 EST Wed, 21 Oct 2020, 11:22:23 EST Wed, 21 Oct 2020, 11:23:19 EST Wed, 21 Oct 2020, 11:58:25 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 1 times in Scopus Search Google Scholar Access Statistics: 52 Abstract Views, 1 File Downloads  -  Detailed Statistics Created: Tue, 20 Oct 2020, 10:37:59 EST

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