# Object Detection on Roboflow-GPR KSLMA

Source: [Object Detection on Roboflow-GPR KSLMA](<https://www.sota2.com/research/sota/object-detection-on-roboflow-gpr-kslma>)

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

Data updated: 2026-04-08T08:27:21.372Z

Evaluation of Object Detection performance on the Roboflow-GPR KSLMA dataset, reporting standard metrics such as Precision, Recall, and mAP@0.5.

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 | Object Detection |
| Dataset (including any stated split) | Roboflow-GPR KSLMA |
| Metric | Precision |
| Unit | PERCENT |
| Direction | Higher is better |
| Results loaded | 2 of 2 |
| 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

- [Precision](<https://www.sota2.com/research/sota/object-detection-on-roboflow-gpr-kslma.md?metric=Precision>): Higher is better; unit: PERCENT.

- [Recall](<https://www.sota2.com/research/sota/object-detection-on-roboflow-gpr-kslma.md?metric=Recall>): Higher is better; unit: PERCENT.

- [mAP@0.5](<https://www.sota2.com/research/sota/object-detection-on-roboflow-gpr-kslma.md?metric=mAP%400.5>): Higher is better; unit: PERCENT.

## Recorded results

| Method | Precision | Result date | Report paper |
| --- | --- | --- | --- |
| WSA-Net | 61.25 | Not recorded | 69d5e0f57d0172140ec7596d |
| YOLOv11n | 56.42 | Not recorded | 69d5e0f57d0172140ec7596d |

### WSA-Net

Precision: 61.25. Result ID: 69d610de47f34ce924be9322.

[Reporting paper](<https://www.sota2.com/research/paper/69d5e0f57d0172140ec7596d.md>)

[Method origin paper](<https://www.sota2.com/research/paper/69d5e0f57d0172140ec7596d.md>)

Recorded evaluation configuration: {"Params(M)":"2.412","FLOPs(G)":"4.2","FPS":"164","Zero-shot":"true"}. This record does not assert independent reproduction.

### YOLOv11n

Precision: 56.42. Result ID: 69d610de47f34ce924be9321.

[Reporting paper](<https://www.sota2.com/research/paper/69d5e0f57d0172140ec7596d.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6cf41e209131cea36cf4.md>)

[Implementation](<https://github.com/IDEACVR/DINO>)

Recorded evaluation configuration: {"Params(M)":"2.583","FLOPs(G)":"6.3","FPS":"152","Zero-shot":"true"}. This record does not assert independent reproduction.

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