Abstract
No public abstract is available from the verified source records.
Contact and support
Need help, have a question, or want to contact the ResearchHub team?
© 2026 ResearchHub. Built for responsible scholarly connection.
Privacy-aware community infrastructureFaysal Ahmmed, Resadus Salehin Rafsan, Muhtadi Mansib, Airin Akther, Ainea Esrat Esika, Mohaimen-Bin-Noor
Abstract
Authors
Institutions
No ROR-resolved institution is linked to this work yet.
Provenance
crossref
Confidence 100%
pubmed
Confidence 98%
unpaywall
Confidence 95%
No local reference links have been materialized yet.
No local citing links have been materialized yet.
A deep learning framework for automated early diagnosis and classification of skin cancer lesions in dermoscopy images
10.1038/s41598-025-15655-9 · 2025
Explainable deep learning approaches for high precision early melanoma detection using dermoscopic images
10.1038/s41598-025-09938-4 · 2025
A fuzzy rank-based deep ensemble methodology for multi-class skin cancer classification
10.1038/s41598-025-90423-3 · 2025
Explainability agreement between dermatologists and five visual explanations techniques in deep neural networks for melanoma ai classification
2023
Deep ensemble learning for multiclass skin lesion classification
10.3390/bioengineering12090934 · 2025
Enhanced melanoma and non-melanoma skin cancer classification using a hybrid LSTM-CNN model
10.1038/s41598-025-08954-8 · 2025
A comprehensive review of deep learning and machine learning techniques for early-stage skin cancer detection: challenges and research gaps
2025
Assessing the generalizability of deep learning models trained on standardized and nonstandardized images and their performance against teledermatologists: Retrospective comparative study
10.2196/35150 · 2022
An explainable hybrid deep learning framework for precise skin lesion segmentation and multi-class classification
datacite
Confidence 0%
2025
Domain shifts in dermoscopic skin cancer datasets: Evaluation of essential limitations for clinical translation
10.1016/j.nbt.2023.04.006 · 2023
10.1109/icscss57650.2023.10169747
10.1109/icscss57650.2023.10169747
SmartSkin-XAI: An interpretable deep learning approach for enhanced skin cancer diagnosis in smart healthcare
10.3390/diagnostics15010064 · 2025
An efficient multi-level pre-processing algorithm for the enhancement of dermoscopy images in melanoma detection
10.1007/s11517-023-02897-w · 2023
Skin cancer classification with deep learning: A systematic review
2022
Transformer-aided skin cancer classification using VGG19-based feature encoding
10.1038/s41598-025-24081-w · 2025
Development and narrow validation of computer vision approach to facilitate assessment of change in pigmented cutaneous lesions
10.1016/j.xjidi.2023.100181 · 2023
A novel vision transformer model for skin cancer classification
10.1007/s11063-023-11204-5 · 2023
Skin cancer classification through quantized color features and generative adversarial network
10.4018/ijaci.2021070104 · 2021
SCDNet: A deep learning-based framework for the multiclassification of skin cancer using dermoscopy images
10.3390/s22155652 · 2022
Classification of melanoma skin cancer based on image data set using different neural networks
10.1038/s41598-024-75143-4 · 2024
Melanoma skin cancer detection using ensemble of machine learning models considering deep feature embeddings
10.1016/j.procs.2024.04.284 · 2024
Vccinet: a multi-model deep learning approach for melanoma skin cancer detection
2024
Melanoma skin cancer identification with explainability utilizing mask guided technique
10.3390/electronics13040680 · 2024
Grad-CAM: Visual explanations from deep networks via gradient-based localization
10.1007/s11263-019-01228-7 · 2020
Unresolved referenced work
2022
Unresolved referenced work
2019
Unresolved referenced work
2013
Unresolved referenced work
2020
Unresolved referenced work
2017
Hair removal and lesion segmentation of dermoscopic images for classification of skin cancer using deep neural networks
2025
Impact of artificial intelligence-based color constancy on dermoscopical assessment of skin lesions: A comparative study
2023
Analysis of dermoscopy images of multi-class for early detection of skin lesions by hybrid systems based on integrating features of CNN models
10.1371/journal.pone.0298305 · 2024
10.1109/cvpr.2017.243
10.1109/cvpr.2017.243
Unresolved referenced work
2021
Unresolved referenced work
2015
Unresolved referenced work
2016
Melanoma classification using a novel deep convolutional neural network with dermoscopic images
10.3390/s22031134 · 2022
Dermoscopic image classification method using an ensemble of fine-tuned convolutional neural networks
10.3390/s22114147 · 2022
Melanoma classification from dermatoscopy images using knowledge distillation for highly imbalanced data
10.1016/j.compbiomed.2023.106571 · 2023
Deep learning for melanoma detection: A deep learning approach to differentiating malignant melanoma from benign melanocytic nevi
10.3390/cancers17010028 · 2025
Enhancing melanoma diagnosis with advanced deep learning models focusing on vision transformer, swin transformer, and ConvNeXt
10.3390/dermatopathology11030026 · doi-reference
Embedded artificial intelligence system using deep learning and raspberry pi for the detection and classification of melanoma
10.11591/ijai.v13.i1.pp1104-1111 · doi-reference