Optical Character Recognition2020en
pendigits
Dataset from Papers With Code
Metrics:accuracy, cer, wer, f1
Current State of the Art
DnC-SC
Unknown
82.27
accuracy
accuracy Progress Over Time
Showing 3 breakthroughs from Jun 2018 to May 2021
Key Milestones
Jun 2018
LBDM
From paper: Large-scale spectral clustering using diffusion coordinates on landmark-based bipartite graphs
74.7
May 2021
DnC-SCCurrent SOTA
From paper: Divide-and-conquer based Large-Scale Spectral Clustering
82.3
+0.7%
Total Improvement
10.1%
Time Span
3y
Breakthroughs
3
Current SOTA
82.3
Top Models Performance Comparison
Top 5 models ranked by accuracy
Best Score
82.3
Top Model
DnC-SC
Models Compared
5
Score Range
8.3
accuracyPrimary
| # | Model | Score | Paper / Code | Date |
|---|---|---|---|---|
| 1 | DnC-SC | 82.27 | Divide-and-conquer based Large-Scale Spectral ClusteringCode | May 2021 |
| 2 | U-SPEC | 81.68 | Apr 2021 | |
| 3 | LSC-R | 81.55 | Apr 2021 | |
| 4 | LBDM | 74.7 | Large-scale spectral clustering using diffusion coordinates on landmark-based bipartite graphs | Jun 2018 |
| 5 | LSC-K | 74.02 | Apr 2021 |
nmi
| # | Model | Score | Paper / Code | Date |
|---|---|---|---|---|
| 1 | DnC-SC | 82.86 | Divide-and-conquer based Large-Scale Spectral ClusteringCode | May 2021 |
| 2 | U-SPEC | 81.68 | Apr 2021 | |
| 3 | LSC-K | 81.37 | Apr 2021 | |
| 4 | LSC-R | 79.15 | Apr 2021 |
runtime-s
| # | Model | Score | Paper / Code | Date |
|---|---|---|---|---|
| 1 | LBDM | 3.08 | Large-scale spectral clustering using diffusion coordinates on landmark-based bipartite graphs | Jun 2018 |
| 2 | U-SPEC | 2.07 | Apr 2021 | |
| 3 | SC_RB | 1.8 | May 2018 | |
| 4 | LSC-K | 1.2 | Apr 2021 | |
| 5 | LSC-R | 0.770 | Apr 2021 | |
| 6 | DnC-SC | 0.640 | Divide-and-conquer based Large-Scale Spectral ClusteringCode | May 2021 |
Related Papers2
Divide-and-conquer based Large-Scale Spectral Clustering
Apr 2021Models: U-SPEC, LSC-R, LSC-K
Scalable Spectral Clustering Using Random Binning Features
May 2018Models: SC_RB