Methods › Computer Vision › Convolutional Neural Networks › LeNet

LeNet

introduced 1998 45 papers tagged archive 2025-07-28

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

LeNet is a classic convolutional neural network employing the use of convolutions, pooling and fully connected layers. It was used for the handwritten digit recognition task with the MNIST dataset. The architectural design served as inspiration for future networks such as AlexNet and VGG..

code

See Code · Elman295/Paper_with_code

Papers archive 2025-07-28

30 shown of 45, 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 50 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 Classification8
image-classification7
Quantization5
Adversarial Robustness3
Data Augmentation3
Deep Learning3
General Classification3
Transfer Learning3
BIG-bench Machine Learning2
Classification2
Clustering2
Diversity2
Knowledge Distillation2
Network Pruning2
Traffic Sign Recognition2
3D Classification1
3D Face Reconstruction1
Adversarial Defense1
All1
Alzheimer's Disease Detection1

Usage over time archive 2025-07-28

Papers per year tagged with LeNet: 2015 to 2023, peak 19 19 0 2015: 1 paper 2015 2016: 6 papers 2016 2017: 5 papers 2017 2018: 5 papers 2018 2019: 19 papers 2019 2020: 7 papers 2020 2021: 1 paper 2021 2022: 0 papers 2022 2023: 1 paper 2023
Papers per year the archive tags with this method, by the paper's archive date (45 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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