Dataset and codes for the paper "No-reference quality assessment of dermoscopic images using minimal expert supervision"
Abstract
Dataset and Source Code for DermaIQA: No-Reference Quality Assessment of Dermoscopic Images This repository contains: Test Dataset - 150 high-quality dermoscopic images - 150 low-quality dermoscopic images Inference Code - Python implementation of DermaIQA - Inference pipeline for quality assessment - Requirements and dependencies - Usage examples (inference.py) Associated with the paper: Ferraris A., Branciforti F., Meiburger K., Veronese F., Zavattaro E., Savoia P., and Salvi M., "No-reference quality assessment of dermoscopic images using minimal expert supervision", Applied Sciences, 2026. Note: The training code and dataset generation pipeline are available upon reasonable request to the corresponding author.
Fields of Study & Subjects
Image and Video Quality Assessment
Cutaneous Melanoma Detection and Management
Digital Media Forensic Detection
Publication details
- Journal / source
- Mendeley Data
- Publication date
- 9 February 2026
- Language
- EN
- Document type
- Dataset