Methods › Computer Vision › Convolutional Neural Networks › ACNN block
Atrous-convolution block
ACNN block
Introduced by Xiao-Yun Zhou et al. in ACNN: a Full Resolution DCNN for Medical Image Segmentation
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Atrous Convolution Neural Network (ACNN), as a pooling-free network structure, is proposed to achieve full-resolution feature processing using a theoretically optimal dilation setting for a larger receptive field, even with fewer parameters. Compared to other techniques, it can achieve higher segmentation Intersection over Union (IoU) and much less trainable parameters and model sizes, indicating the benefit of full-resolution feature maps in feature processing.
Papers archive 2025-07-28
2 shown of 2, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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Deep learning-based rapid generation of broadly reactive antibodies against SARS-CoV-2 and its Omicron variant 27 Sep 2022 · 1 repository
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ACNN: a Full Resolution DCNN for Medical Image Segmentation 26 Jan 2019 · 1 repository · arXiv:1901.09203
Tasks archive 2025-07-28
8 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
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