# A lightweight YOLO11n seg framework for real time surface crack detection with segmentation

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/a-lightweight-yolo11n-seg-framework-for-real-time-surface-crack-detection-with/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Shweta Tiwari,Kamal Kumar Gola,Rohit Kanauzia,Gopal Kumar Gupta |
| Citations | 4 |
| DOI | 10.1038/s41598-026-37073-1 |
| Fields | Computer Science,Engineering |
| Open Access | true |
| OA Status | gold |
| OA URL | https://www.nature.com/articles/s41598-026-37073-1_reference.pdf |
| OpenAlex ID | https://openalex.org/W7126052602 |
| PMID | 41611793 |
| Type | article |
| Year | 2026 |

## Paper authors

- [Rohit Kanauzia](https://scholariq.org/researchers/rohit-kanauzia/)

## Paper journal

- [Scientific Reports](https://scholariq.org/journals/scientific-reports/)

## Paper primary topic

- [Infrastructure Maintenance and Monitoring](https://scholariq.org/topics/infrastructure-maintenance-and-monitoring/)

## Paper topics

- [Infrastructure Maintenance and Monitoring](https://scholariq.org/topics/infrastructure-maintenance-and-monitoring/)
- [Advanced Neural Network Applications](https://scholariq.org/topics/advanced-neural-network-applications/)
- [Concrete Corrosion and Durability](https://scholariq.org/topics/concrete-corrosion-and-durability/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.