# Monkeypox Image Data collection

arXiv: https://arxiv.org/abs/2206.01774 · HTML: https://mlsanity.com/paper/2206.01774/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 7 references that are in the map.
- First posted on arXiv 3 Jun 2022.

## Builds on (most cited first, 1 of 1)

- [COVID-19 Image Data Collection](https://mlsanity.com/paper/2003.11597/) (2020)

## Built on by (most cited first, 6 of 6)

- [A Web-based Mpox Skin Lesion Detection System Using State-of-the-art Deep Learning Models Considering Racial Diversity](https://mlsanity.com/paper/2306.14169/) (2023)
- [Monkeypox virus detection using pre-trained deep learning-based approaches](https://mlsanity.com/paper/2209.04444/) (2022)
- [Transfer learning and Local interpretable model agnostic based visual approach in Monkeypox Disease Detection and Classification: A Deep Learning insights](https://mlsanity.com/paper/2211.05633/) (2022)
- [MpoxVLM: A Vision-Language Model for Diagnosing Skin Lesions from Mpox Virus Infection](https://mlsanity.com/paper/2411.10888/) (2024)
- [A Transfer Learning and Explainable Solution to Detect mpox from Smartphones images](https://mlsanity.com/paper/2305.18489/) (2023)
- [A Comparative Analysis of CNN-Based Pretrained Models for the Detection and Prediction of Monkeypox](https://mlsanity.com/paper/2302.10277/) (2023)

## Abstract (arXiv)

This paper explains the initial Monkeypox Open image data collection procedure. It was created by assembling images collected from websites, newspapers, and online portals and currently contains around 1905 images after data augmentation.