# Image Classification on CIFAR-10-C Gaussian Noise (test)

Source: [Image Classification on CIFAR-10-C Gaussian Noise (test)](<https://www.sota2.com/research/sota/image-classification-on-cifar-10-c-gaussian-noise-test>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-04-07T07:15:45.042Z

Evaluation of Image Classification performance on the test split of CIFAR-10 corrupted specifically by Gaussian Noise.

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

| Scope | Recorded value |
| --- | --- |
| Task | Image Classification |
| Dataset (including any stated split) | CIFAR-10-C Gaussian Noise (test) |
| Metric | Accuracy |
| Unit | PERCENT |
| Direction | Higher is better |
| Results loaded | 5 of 5 |
| Coverage | All results currently returned for this benchmark |

Evaluation settings may differ between results. The original papers and recorded configurations are needed to establish comparability. A shared metric name alone does not establish an identical protocol.

## Metrics

- [Accuracy](<https://www.sota2.com/research/sota/image-classification-on-cifar-10-c-gaussian-noise-test.md?metric=Accuracy>): Higher is better; unit: PERCENT.

## Recorded results

| Method | Accuracy | Result date | Report paper |
| --- | --- | --- | --- |
| TM-NORM | 74.82 | Not recorded | 68fa78801e209131cea78b7c |
| TM-NORM | 53.28 | Not recorded | 68fa78801e209131cea78b7c |
| Learnable threshold | 51.86 | Not recorded | 68fa78801e209131cea78b7c |
| Learnable threshold | 49.25 | Not recorded | 68fa78801e209131cea78b7c |
| Adaptive LIF | 31.62 | Not recorded | 68fa78801e209131cea78b7c |

### TM-NORM

Accuracy: 74.82. Result ID: 69d4adf747f34ce924bc01b7.

[Reporting paper](<https://www.sota2.com/research/paper/68fa78801e209131cea78b7c.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa78801e209131cea78b7c.md>)

Recorded evaluation configuration: {"Backbone":"Spiking ResNet-20","Evaluation Protocol":"Adaptation"}. This record does not assert independent reproduction.

### TM-NORM

Accuracy: 53.28. Result ID: 69d4adf747f34ce924bc01b6.

[Reporting paper](<https://www.sota2.com/research/paper/68fa78801e209131cea78b7c.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa78801e209131cea78b7c.md>)

Recorded evaluation configuration: {"Backbone":"Spiking ResNet-20","Evaluation Protocol":"Source"}. This record does not assert independent reproduction.

### Learnable threshold

Accuracy: 51.86. Result ID: 69d4adf747f34ce924bc01b4.

[Reporting paper](<https://www.sota2.com/research/paper/68fa78801e209131cea78b7c.md>)

Recorded evaluation configuration: {"Backbone":"Spiking ResNet-20","Evaluation Protocol":"Source"}. This record does not assert independent reproduction.

### Learnable threshold

Accuracy: 49.25. Result ID: 69d4adf747f34ce924bc01b5.

[Reporting paper](<https://www.sota2.com/research/paper/68fa78801e209131cea78b7c.md>)

Recorded evaluation configuration: {"Backbone":"Spiking ResNet-20","Evaluation Protocol":"Adaptation"}. This record does not assert independent reproduction.

### Adaptive LIF

Accuracy: 31.62. Result ID: 69d4adf747f34ce924bc01b3.

[Reporting paper](<https://www.sota2.com/research/paper/68fa78801e209131cea78b7c.md>)

Recorded evaluation configuration: {"Backbone":"Spiking ResNet-20","Evaluation Protocol":"Source"}. This record does not assert independent reproduction.

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