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Dilated Bottleneck Block

5 papers tagged archive 2025-07-28

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

Dilated Bottleneck Block is an image model block used in the DetNet convolutional neural network architecture. It employs a bottleneck structure with dilated convolutions to efficiently enlarge the receptive field.

Source: DetNet: A Backbone network for Object DetectionSee Code · tsing-cv/DetNet

Papers archive 2025-07-28

5 shown of 5, 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

11 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
Classification2
General Classification2
Image Classification2
Instance Segmentation2
Object2
Object Detection2
Semantic Segmentation2
image-classification2
object-detection2
valid2
Deep Learning1

Usage over time archive 2025-07-28

Papers per year tagged with Dilated Bottleneck Block: 2018 to 2021, peak 2 2 0 2018: 2 papers 2018 2019: 1 paper 2019 2020: 1 paper 2020 2021: 1 paper 2021
Papers per year the archive tags with this method, by the paper's archive date (5 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 Connection Blocks

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