Methods › Computer Vision › Semantic Segmentation Modules › DASPP

Deeper Atrous Spatial Pyramid Pooling

DASPP

1 paper tagged archive 2025-07-28

Introduced by Taha Emara et al. in LiteSeg: A Novel Lightweight ConvNet for Semantic Segmentation

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

DASPP is a deeper version of the ASPP module (the latter from DeepLabv3) that adds standard 3 × 3 convolution after 3 × 3 dilated convolutions to refine the features and also fusing the input and the output of the DASPP module via short residual connection. Also, the number of convolution filters of ASPP is reduced from 255 to 96 to gain computational performance.

PaperSource

Papers archive 2025-07-28

1 shown of 1, 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.

Tasks archive 2025-07-28

6 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Computational Efficiency1
Image Segmentation1
Medical Image Analysis1
Real-Time Semantic Segmentation1
Segmentation1
Semantic Segmentation1

Usage over time archive 2025-07-28

Papers per year tagged with DASPP: 2019 to 2019, peak 1 1 0 2019: 1 paper 2019
Papers per year the archive tags with this method, by the paper's archive date (1 dated). Bars are counts, not a trend claim.

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

Semantic Segmentation Modules

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