Methods › Computer Vision › Image Model Blocks › Reduction-A

Reduction-A

28 papers tagged archive 2025-07-28

Introduced by Christian Szegedy et al. in Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning

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

Reduction-A is an image model block used in the Inception-v4 architecture.

PaperSourceSee Code · Cadene/pretrained-models.pytorch

Papers archive 2025-07-28

28 shown of 28, 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 58 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
Transfer Learning6
General Classification5
Image Classification4
Classification3
Decoder3
Segmentation3
Image Segmentation2
Lesion Segmentation2
Machine Translation2
Meta-Learning2
Object2
Semantic Segmentation2
3D Reconstruction1
Action Recognition1
Activity Recognition1
All1
Breast Cancer Detection1
Caption Generation1
Classifier calibration1
Colorization1

Usage over time archive 2025-07-28

Papers per year tagged with Reduction-A: 2016 to 2025, peak 6 6 0 2016: 2 papers 2016 2017: 3 papers 2017 2018: 2 papers 2018 2019: 4 papers 2019 2020: 6 papers 2020 2021: 1 paper 2021 2022: 4 papers 2022 2023: 1 paper 2023 2024: 3 papers 2024 2025: 2 papers 2025
Papers per year the archive tags with this method, by the paper's archive date (28 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

Image Model Blocks

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