Methods › Computer Vision › Convolutional Neural Networks › CSPDenseNet-Elastic

CSPDenseNet-Elastic

1 paper tagged archive 2025-07-28

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

CSPDenseNet-Elastic is a convolutional neural network and object detection backbone where we apply the Cross Stage Partial Network (CSPNet) approach to DenseNet-Elastic. The CSPNet partitions the feature map of the base layer into two parts and then merges them through a cross-stage hierarchy. The use of a split and merge strategy allows for more gradient flow through the network.

Source: CSPNet: A New Backbone that can Enhance Learning...

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

4 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
Attribute1
Image Classification1
Object Detection1
Real-Time Object Detection1

Usage over time archive 2025-07-28

Papers per year tagged with CSPDenseNet-Elastic: 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

Convolutional Neural Networks

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