SkinDWNet: a novel deep learning model for multiclass classification of skin cancers using dermoscopic images
Ahmad Naeem(Muhammad Nawaz Sharif University of Engineering & Technology), Rizwan Ali Naqvi(Sejong University), Mui-zzud- din(Ghazi University), Hassaan Malik(National College of Business Administration and Economics), Abolghasem Sadeghi‐Niaraki(Sejong University), Daesik Jeong(Sangmyung University)
Cited by 5
Related Papers
DSCC_Net: Multi-Classification Deep Learning Models for Diagnosing of Skin Cancer Using Dermoscopic Images
|Cancers|2023|213
Malignant Melanoma Classification Using Deep Learning: Datasets, Performance Measurements, Challenges and Opportunities
|IEEE Access|2020|182
SCDNet: A Deep Learning-Based Framework for the Multiclassification of Skin Cancer Using Dermoscopy Images
|Sensors|2022|119
CDC_Net: multi-classification convolutional neural network model for detection of COVID-19, pneumothorax, pneumonia, lung Cancer, and tuberculosis using chest X-rays
|Multimedia Tools and Applications|2022|118
A Comprehensive Analysis of Recent Deep and Federated-Learning-Based Methodologies for Brain Tumor Diagnosis
|Journal of Personalized Medicine|2022|101