Methods › Computer Vision › Convolutional Neural Networks › VGG-19

Visual Geometry Group 19 Layer CNN

VGG-19

87 papers tagged archive 2025-07-28

Introduced by Karen Simonyan et al. in Very Deep Convolutional Networks for Large-Scale Image Recognition

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

The archive carries no description for this method.

PaperSource

Papers archive 2025-07-28

30 shown of 87, 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 96 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 Learning19
Image Classification14
image-classification13
General Classification8
Classification7
Deep Learning6
GPU6
Semantic Segmentation4
Binary Classification3
Diagnostic3
Network Pruning3
Object Detection3
Object Recognition3
Prognosis3
Segmentation3
Autonomous Driving2
BIG-bench Machine Learning2
CPU2
Cell Segmentation2
Data Augmentation2

Usage over time archive 2025-07-28

Papers per year tagged with VGG-19: 2014 to 2025, peak 16 16 0 2014: 1 paper 2014 2015: 0 papers 2015 2016: 1 paper 2016 2017: 0 papers 2017 2018: 9 papers 2018 2019: 16 papers 2019 2020: 10 papers 2020 2021: 14 papers 2021 2022: 6 papers 2022 2023: 14 papers 2023 2024: 10 papers 2024 2025: 6 papers 2025
Papers per year the archive tags with this method, by the paper's archive date (87 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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