Multimodal deep learning framework for automated acne diagnosis: detection, lesion localization, classification, and severity assessment
Authors:
- Rachna SinghRSRachna Singh
- Atman JadonAJAtman Jadon
- Rupinder KaurRKRupinder Kaur
- Glory Nicholson ParmarGPGlory Nicholson Parmar
- Akash BiswasABAkash Biswas
- Harsh SaxenaHSHarsh Saxena
- Khushal NagalKNKhushal Nagal
- Dhriti KakkarDKDhriti Kakkar
- Harleen KaurHKHarleen Kaur
- Prashant JindalPJPrashant Jindal
- Mamta JunejaMJMamta Juneja
- 25 October 2026
- journal article
- Published by Elsevier in Biomedical Signal Processing and Control
- Vol. 131
Abstract
No abstract availableThis publication has 24 references indexed in Scilit:
- Retinal Diabetic Macular Edema Detection in OCT Images Using DeepLabv3 + with ResNet-18 ArchitectureSensing and Imaging, 2026
- ACNE84-Alpha: An AI-Based System for Acne Detection, Differential Diagnosis, and Severity Evaluation2025
- A Redundancy Free Facial Acne Detection Framework Based on Multi-view Face Images Stitching2025
- A smart facial acne disease monitoring for automate severity assessment using AI-enabled cloud-based internet of thingsDiscover Computing, 2025
- Severity level prediction of acne using hybrid MOA-FCM segmentation algorithm with ANN classifierProgress in Artificial Intelligence, 2024
- Identification of wart treatment evaluation by using optimum ensemble based classification techniquesBiomedical Signal Processing and Control, 2024
- Cystic acne treatment: A comprehensive reviewMedicine Advances, 2023
- A cell phone app for facial acne severity assessmentApplied Intelligence, 2022
- Pustules2013
- Dermatology2011