Methods › Computer Vision › Convolutional Neural Networks › VGG-16

VGG-16

46 papers tagged archive 2025-07-28

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

The archive carries no description for this method.

Source: Very Deep Convolutional Networks for Large-Scale Image...

Papers archive 2025-07-28

30 shown of 46, 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 67 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
Image Classification11
Transfer Learning11
Classification8
image-classification8
Data Augmentation3
Decision Making3
Deep Learning3
Activity Recognition2
Explainable artificial intelligence2
Human Activity Recognition2
Image Enhancement2
Management2
Medical Diagnosis2
Medical Image Analysis2
Medical Image Classification2
Remote Sensing Image Classification2
Segmentation2
Sensitivity2
Time Series2
Time Series Classification2

Usage over time archive 2025-07-28

Papers per year tagged with VGG-16: 2014 to 2025, peak 21 21 0 2014: 1 paper 2014 2015: 0 papers 2015 2016: 0 papers 2016 2017: 0 papers 2017 2018: 0 papers 2018 2019: 0 papers 2019 2020: 2 papers 2020 2021: 7 papers 2021 2022: 1 paper 2022 2023: 1 paper 2023 2024: 21 papers 2024 2025: 13 papers 2025
Papers per year the archive tags with this method, by the paper's archive date (46 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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