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SotA/Computer Vision/Image Classification/MNIST

Image Classification on MNIST

Metric: Trainable Parameters (higher is better)

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Results

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#Model↕Trainable Parameters▼Extra DataPaperDate↕Code
1Neural Architecture Search (NAS)-enabled Convolutional Neural Network (CNN)1882602No---
2Branching/Merging CNN + Homogeneous Vector Capsules1514187NoNo Routing Needed Between Capsules2020-01-24Code
3SOPCNN (Only a single Model)1400000NoStochastic Optimization of Plain Convolutional N...2020-01-24Code
4ViT-Mini_D91208586No---
5R-ExplaiNet-22 (single model)743882NoLearning local discrete features in explainable-...2024-10-31Code
6DNN-5 (Trainable Activations)575051No--Code
7ExquisiteNetV2518230NoA Novel lightweight Convolutional Neural Network...2021-05-19Code
8TAAF-CNN421642No--Code
9DNN-3 (Trainable Activations)386719No--Code
10DNN-2 (Trainable Activations)311651No--Code
11Efficient-CapsNet161824NoEfficient-CapsNet: Capsule Network with Self-Att...2021-01-29Code
12Convolutional PMM (Parametric Matrix Model)129416NoParametric Matrix Models2024-01-22-
13PMM (Parametric Matrix Model)4990NoParametric Matrix Models2024-01-22-