Methods › Computer Vision › Convolutional Neural Networks › SpineNet

SpineNet

5 papers tagged archive 2025-07-28

Introduced by Xianzhi Du et al. in SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization

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

SpineNet is a convolutional neural network backbone with scale-permuted intermediate features and cross-scale connections that is learned on an object detection task by Neural Architecture Search.

Paper Source See Code · lucifer443/SpineNet-Pytorch

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.

SpineNetV2: Automated Detection, Labelling and Radiological Grading Of Clinical MR Scans
3 May 2022 · 0 repositories · arXiv:2205.01683
Efficient Scale-Permuted Backbone with Learned Resource Distribution
22 Oct 2020 · 0 repositories · arXiv:2010.11426
Rethinking Pre-training and Self-training
11 Jun 2020 · 2 repositories · arXiv:2006.06882
Evolving Normalization-Activation Layers
6 Apr 2020 · 8 repositories · arXiv:2004.02967

Syntology ran 3 of 5 samples · 2 unverified · 3 pointer-only (licence)
SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization
10 Dec 2019 · 13 repositories · arXiv:1912.05027

Tasks archive 2025-07-28

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

Task	Papers
Image Classification	3
Object Detection	3
Semantic Segmentation	3
object-detection	3
Instance Segmentation	2
image-classification	2
Body Detection	1
Data Augmentation	1
General Classification	1
Image Generation	1
Neural Architecture Search	1
Object	1
Point Cloud Registration	1
Real-Time Object Detection	1
Segmentation	1

Usage over time archive 2025-07-28

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

Convolutional Neural Networks

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