Methods › Computer Vision › Light-weight neural networks › MixNet

MixNet

12 papers tagged archive 2025-07-28

Introduced by Mingxing Tan et al. in MixConv: Mixed Depthwise Convolutional Kernels

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

MixNet is a type of convolutional neural network discovered via AutoML that utilises MixConvs instead of regular depthwise convolutions.

PaperSourceSee Code · osmr/imgclsmob

Papers archive 2025-07-28

12 shown of 12, 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 33 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 Classification3
Object2
AutoML1
Automatic Speech Recognition1
Automatic Speech Recognition (ASR)1
Benchmarking1
Brain Computer Interface1
Classification1
Data Augmentation1
Deblurring1
Diagnostic1
EEG1
Fault Diagnosis1
Image Deblurring1
Image Enhancement1
Image Restoration1
Image Steganography1
Low-Light Image Enhancement1
Mixture-of-Experts1
Motor Imagery1

Usage over time archive 2025-07-28

Papers per year tagged with MixNet: 2019 to 2024, peak 4 4 0 2019: 1 paper 2019 2020: 3 papers 2020 2021: 2 papers 2021 2022: 1 paper 2022 2023: 1 paper 2023 2024: 4 papers 2024
Papers per year the archive tags with this method, by the paper's archive date (12 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

Light-weight neural networksConvolutional Neural Networks

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