Deep Learning–Based Methods for Automatic Diagnosis of Skin Lesions
The main purpose of the study was to develop a high accuracy system able to diagnose skin lesions using deep learning−based methods. We propose a new decision system based on multiple classifiers like neural networks and feature−based methods. Each classifier (method) gives the f...
Main Authors: | Hassan El-Khatib, Dan Popescu, Loretta Ichim |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-03-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/20/6/1753 |
Similar Items
-
Integration of Localized, Contextual, and Hierarchical Features in Deep Learning for Improved Skin Lesion Classification
by: Karthik Ramamurthy, et al.
Published: (2024-06-01) -
Dense-Residual Network With Adversarial Learning for Skin Lesion Segmentation
by: Wenli Tu, et al.
Published: (2019-01-01) -
Two-stage Skin Lesion Segmentation from Dermoscopic Images by Using Deep Neural Networks
by: Fatemeh Bagheri, et al.
Published: (2020-07-01) -
A Hybrid Deep Learning Approach for Skin Cancer Classification Using Swin Transformer and Dense Group Shuffle Non-Local Attention Network
by: R. Karthik, et al.
Published: (2024-01-01) -
Deep Learning Can Improve Early Skin Cancer Detection
by: Abeer Mohamed, et al.
Published: (2019-09-01)