Methods › General › Skip Connections › Concatenated Skip Connection

Concatenated Skip Connection

3,337 papers tagged archive 2025-07-28

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

A Concatenated Skip Connection is a type of skip connection that seeks to reuse features by concatenating them to new layers, allowing more information to be retained from previous layers of the network. This contrasts with say, residual connections, where element-wise summation is used instead to incorporate information from previous layers. This type of skip connection is prominently used in DenseNets (and also Inception networks), which the Figure to the right illustrates.

See Code · pytorch/vision

Papers archive 2025-07-28

30 shown of 3,337, 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

20 shown of 955 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
Segmentation896
Semantic Segmentation715
Image Segmentation466
Decoder282
Medical Image Segmentation274
Denoising182
Deep Learning174
Image Generation150
Image Classification135
Data Augmentation130
Tumor Segmentation128
Transfer Learning118
image-classification118
Diagnostic116
Classification103
General Classification98
Computed Tomography (CT)93
Generative Adversarial Network85
Medical Image Analysis83
Super-Resolution83

Usage over time archive 2025-07-28

Papers per year tagged with Concatenated Skip Connection: 2015 to 2025, peak 646 646 0 2015: 3 papers 2015 2016: 5 papers 2016 2017: 55 papers 2017 2018: 185 papers 2018 2019: 310 papers 2019 2020: 442 papers 2020 2021: 451 papers 2021 2022: 438 papers 2022 2023: 521 papers 2023 2024: 646 papers 2024 2025: 281 papers 2025
Papers per year the archive tags with this method, by the paper's archive date (3,337 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

Skip Connections

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