# Melanoma Lesion Detection and Segmentation Using YOLOv4-DarkNet and Active Contour

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/melanoma-lesion-detection-and-segmentation-using-yolov4-darknet-and-active/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Saleh Albahli,Nudrat Nida,Aun Irtaza,Muhammad Haroon Yousaf,Muhammad Tariq Mahmood |
| Citations | 124 |
| DOI | 10.1109/access.2020.3035345 |
| Fields | Computer Science,Medicine |
| Open Access | true |
| OA Status | gold |
| OA URL | https://ieeexplore.ieee.org/ielx7/6287639/8948470/09247186.pdf |
| OpenAlex ID | https://openalex.org/W3094961137 |
| Type | article |
| Year | 2020 |

## Paper authors

- [Saleh Albahli](https://scholariq.org/researchers/saleh-albahli/)

## Paper journal

- [IEEE Access](https://scholariq.org/journals/ieee-access/)

## Paper primary topic

- [Cutaneous Melanoma Detection and Management](https://scholariq.org/topics/cutaneous-melanoma-detection-and-management/)

## Paper topics

- [Cutaneous Melanoma Detection and Management](https://scholariq.org/topics/cutaneous-melanoma-detection-and-management/)
- [AI in cancer detection](https://scholariq.org/topics/ai-in-cancer-detection/)
- [Infrared Thermography in Medicine](https://scholariq.org/topics/infrared-thermography-in-medicine/)

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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.